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Understanding Data Presentations (Guide + Examples)

In this age of overwhelming information, the skill to effectively convey data has become extremely valuable. Initiating a discussion on data presentation types involves thoughtful consideration of the nature of your data and the message you aim to convey. Different types of visualizations serve distinct purposes. Whether you’re dealing with how to develop a report or simply trying to communicate complex information, how you present data influences how well your audience understands and engages with it. This extensive guide leads you through the different ways of data presentation.

Table of Contents

What is a Data Presentation?

What should a data presentation include, line graphs, treemap chart, scatter plot, how to choose a data presentation type, recommended data presentation templates, common mistakes done in data presentation.

A data presentation is a slide deck that aims to disclose quantitative information to an audience through the use of visual formats and narrative techniques derived from data analysis, making complex data understandable and actionable. This process requires a series of tools, such as charts, graphs, tables, infographics, dashboards, and so on, supported by concise textual explanations to improve understanding and boost retention rate.

Data presentations require us to cull data in a format that allows the presenter to highlight trends, patterns, and insights so that the audience can act upon the shared information. In a few words, the goal of data presentations is to enable viewers to grasp complicated concepts or trends quickly, facilitating informed decision-making or deeper analysis.

Data presentations go beyond the mere usage of graphical elements. Seasoned presenters encompass visuals with the art of data storytelling , so the speech skillfully connects the points through a narrative that resonates with the audience. Depending on the purpose – inspire, persuade, inform, support decision-making processes, etc. – is the data presentation format that is better suited to help us in this journey.

To nail your upcoming data presentation, ensure to count with the following elements:

• Clear Objectives: Understand the intent of your presentation before selecting the graphical layout and metaphors to make content easier to grasp.
• Engaging introduction: Use a powerful hook from the get-go. For instance, you can ask a big question or present a problem that your data will answer. Take a look at our guide on how to start a presentation for tips & insights.
• Structured Narrative: Your data presentation must tell a coherent story. This means a beginning where you present the context, a middle section in which you present the data, and an ending that uses a call-to-action. Check our guide on presentation structure for further information.
• Visual Elements: These are the charts, graphs, and other elements of visual communication we ought to use to present data. This article will cover one by one the different types of data representation methods we can use, and provide further guidance on choosing between them.
• Insights and Analysis: This is not just showcasing a graph and letting people get an idea about it. A proper data presentation includes the interpretation of that data, the reason why it’s included, and why it matters to your research.
• Conclusion & CTA: Ending your presentation with a call to action is necessary. Whether you intend to wow your audience into acquiring your services, inspire them to change the world, or whatever the purpose of your presentation, there must be a stage in which you convey all that you shared and show the path to staying in touch. Plan ahead whether you want to use a thank-you slide, a video presentation, or which method is apt and tailored to the kind of presentation you deliver.
• Q&A Session: After your speech is concluded, allocate 3-5 minutes for the audience to raise any questions about the information you disclosed. This is an extra chance to establish your authority on the topic. Check our guide on questions and answer sessions in presentations here.

Bar charts are a graphical representation of data using rectangular bars to show quantities or frequencies in an established category. They make it easy for readers to spot patterns or trends. Bar charts can be horizontal or vertical, although the vertical format is commonly known as a column chart. They display categorical, discrete, or continuous variables grouped in class intervals [1] . They include an axis and a set of labeled bars horizontally or vertically. These bars represent the frequencies of variable values or the values themselves. Numbers on the y-axis of a vertical bar chart or the x-axis of a horizontal bar chart are called the scale.

Real-Life Application of Bar Charts

Let’s say a sales manager is presenting sales to their audience. Using a bar chart, he follows these steps.

Step 1: Selecting Data

The first step is to identify the specific data you will present to your audience.

The sales manager has highlighted these products for the presentation.

• Product A: Men’s Shoes
• Product B: Women’s Apparel
• Product C: Electronics
• Product D: Home Decor

Step 2: Choosing Orientation

Opt for a vertical layout for simplicity. Vertical bar charts help compare different categories in case there are not too many categories [1] . They can also help show different trends. A vertical bar chart is used where each bar represents one of the four chosen products. After plotting the data, it is seen that the height of each bar directly represents the sales performance of the respective product.

It is visible that the tallest bar (Electronics – Product C) is showing the highest sales. However, the shorter bars (Women’s Apparel – Product B and Home Decor – Product D) need attention. It indicates areas that require further analysis or strategies for improvement.

Step 3: Colorful Insights

Different colors are used to differentiate each product. It is essential to show a color-coded chart where the audience can distinguish between products.

• Men’s Shoes (Product A): Yellow
• Women’s Apparel (Product B): Orange
• Electronics (Product C): Violet
• Home Decor (Product D): Blue

Bar charts are straightforward and easily understandable for presenting data. They are versatile when comparing products or any categorical data [2] . Bar charts adapt seamlessly to retail scenarios. Despite that, bar charts have a few shortcomings. They cannot illustrate data trends over time. Besides, overloading the chart with numerous products can lead to visual clutter, diminishing its effectiveness.

For more information, check our collection of bar chart templates for PowerPoint .

Line graphs help illustrate data trends, progressions, or fluctuations by connecting a series of data points called ‘markers’ with straight line segments. This provides a straightforward representation of how values change [5] . Their versatility makes them invaluable for scenarios requiring a visual understanding of continuous data. In addition, line graphs are also useful for comparing multiple datasets over the same timeline. Using multiple line graphs allows us to compare more than one data set. They simplify complex information so the audience can quickly grasp the ups and downs of values. From tracking stock prices to analyzing experimental results, you can use line graphs to show how data changes over a continuous timeline. They show trends with simplicity and clarity.

Real-life Application of Line Graphs

To understand line graphs thoroughly, we will use a real case. Imagine you’re a financial analyst presenting a tech company’s monthly sales for a licensed product over the past year. Investors want insights into sales behavior by month, how market trends may have influenced sales performance and reception to the new pricing strategy. To present data via a line graph, you will complete these steps.

First, you need to gather the data. In this case, your data will be the sales numbers. For example:

• January: $45,000
• February: $55,000
• March: $45,000
• April: $60,000
• May: $ 70,000
• June: $65,000
• July: $62,000
• August: $68,000
• September: $81,000
• October: $76,000
• November: $87,000
• December: $91,000

After choosing the data, the next step is to select the orientation. Like bar charts, you can use vertical or horizontal line graphs. However, we want to keep this simple, so we will keep the timeline (x-axis) horizontal while the sales numbers (y-axis) vertical.

Step 3: Connecting Trends

After adding the data to your preferred software, you will plot a line graph. In the graph, each month’s sales are represented by data points connected by a line.

Step 4: Adding Clarity with Color

If there are multiple lines, you can also add colors to highlight each one, making it easier to follow.

Line graphs excel at visually presenting trends over time. These presentation aids identify patterns, like upward or downward trends. However, too many data points can clutter the graph, making it harder to interpret. Line graphs work best with continuous data but are not suitable for categories.

For more information, check our collection of line chart templates for PowerPoint and our article about how to make a presentation graph .

A data dashboard is a visual tool for analyzing information. Different graphs, charts, and tables are consolidated in a layout to showcase the information required to achieve one or more objectives. Dashboards help quickly see Key Performance Indicators (KPIs). You don’t make new visuals in the dashboard; instead, you use it to display visuals you’ve already made in worksheets [3] .

Keeping the number of visuals on a dashboard to three or four is recommended. Adding too many can make it hard to see the main points [4]. Dashboards can be used for business analytics to analyze sales, revenue, and marketing metrics at a time. They are also used in the manufacturing industry, as they allow users to grasp the entire production scenario at the moment while tracking the core KPIs for each line.

Real-Life Application of a Dashboard

Consider a project manager presenting a software development project’s progress to a tech company’s leadership team. He follows the following steps.

Step 1: Defining Key Metrics

To effectively communicate the project’s status, identify key metrics such as completion status, budget, and bug resolution rates. Then, choose measurable metrics aligned with project objectives.

Step 2: Choosing Visualization Widgets

After finalizing the data, presentation aids that align with each metric are selected. For this project, the project manager chooses a progress bar for the completion status and uses bar charts for budget allocation. Likewise, he implements line charts for bug resolution rates.

Step 3: Dashboard Layout

Key metrics are prominently placed in the dashboard for easy visibility, and the manager ensures that it appears clean and organized.

Dashboards provide a comprehensive view of key project metrics. Users can interact with data, customize views, and drill down for detailed analysis. However, creating an effective dashboard requires careful planning to avoid clutter. Besides, dashboards rely on the availability and accuracy of underlying data sources.

For more information, check our article on how to design a dashboard presentation , and discover our collection of dashboard PowerPoint templates .

Treemap charts represent hierarchical data structured in a series of nested rectangles [6] . As each branch of the ‘tree’ is given a rectangle, smaller tiles can be seen representing sub-branches, meaning elements on a lower hierarchical level than the parent rectangle. Each one of those rectangular nodes is built by representing an area proportional to the specified data dimension.

Treemaps are useful for visualizing large datasets in compact space. It is easy to identify patterns, such as which categories are dominant. Common applications of the treemap chart are seen in the IT industry, such as resource allocation, disk space management, website analytics, etc. Also, they can be used in multiple industries like healthcare data analysis, market share across different product categories, or even in finance to visualize portfolios.

Real-Life Application of a Treemap Chart

Let’s consider a financial scenario where a financial team wants to represent the budget allocation of a company. There is a hierarchy in the process, so it is helpful to use a treemap chart. In the chart, the top-level rectangle could represent the total budget, and it would be subdivided into smaller rectangles, each denoting a specific department. Further subdivisions within these smaller rectangles might represent individual projects or cost categories.

Step 1: Define Your Data Hierarchy

While presenting data on the budget allocation, start by outlining the hierarchical structure. The sequence will be like the overall budget at the top, followed by departments, projects within each department, and finally, individual cost categories for each project.

• Top-level rectangle: Total Budget
• Second-level rectangles: Departments (Engineering, Marketing, Sales)
• Third-level rectangles: Projects within each department
• Fourth-level rectangles: Cost categories for each project (Personnel, Marketing Expenses, Equipment)

Step 2: Choose a Suitable Tool

It’s time to select a data visualization tool supporting Treemaps. Popular choices include Tableau, Microsoft Power BI, PowerPoint, or even coding with libraries like D3.js. It is vital to ensure that the chosen tool provides customization options for colors, labels, and hierarchical structures.

Here, the team uses PowerPoint for this guide because of its user-friendly interface and robust Treemap capabilities.

Step 3: Make a Treemap Chart with PowerPoint

After opening the PowerPoint presentation, they chose “SmartArt” to form the chart. The SmartArt Graphic window has a “Hierarchy” category on the left.  Here, you will see multiple options. You can choose any layout that resembles a Treemap. The “Table Hierarchy” or “Organization Chart” options can be adapted. The team selects the Table Hierarchy as it looks close to a Treemap.

Step 5: Input Your Data

After that, a new window will open with a basic structure. They add the data one by one by clicking on the text boxes. They start with the top-level rectangle, representing the total budget.  

Step 6: Customize the Treemap

By clicking on each shape, they customize its color, size, and label. At the same time, they can adjust the font size, style, and color of labels by using the options in the “Format” tab in PowerPoint. Using different colors for each level enhances the visual difference.

Treemaps excel at illustrating hierarchical structures. These charts make it easy to understand relationships and dependencies. They efficiently use space, compactly displaying a large amount of data, reducing the need for excessive scrolling or navigation. Additionally, using colors enhances the understanding of data by representing different variables or categories.

In some cases, treemaps might become complex, especially with deep hierarchies.  It becomes challenging for some users to interpret the chart. At the same time, displaying detailed information within each rectangle might be constrained by space. It potentially limits the amount of data that can be shown clearly. Without proper labeling and color coding, there’s a risk of misinterpretation.

A heatmap is a data visualization tool that uses color coding to represent values across a two-dimensional surface. In these, colors replace numbers to indicate the magnitude of each cell. This color-shaded matrix display is valuable for summarizing and understanding data sets with a glance [7] . The intensity of the color corresponds to the value it represents, making it easy to identify patterns, trends, and variations in the data.

As a tool, heatmaps help businesses analyze website interactions, revealing user behavior patterns and preferences to enhance overall user experience. In addition, companies use heatmaps to assess content engagement, identifying popular sections and areas of improvement for more effective communication. They excel at highlighting patterns and trends in large datasets, making it easy to identify areas of interest.

We can implement heatmaps to express multiple data types, such as numerical values, percentages, or even categorical data. Heatmaps help us easily spot areas with lots of activity, making them helpful in figuring out clusters [8] . When making these maps, it is important to pick colors carefully. The colors need to show the differences between groups or levels of something. And it is good to use colors that people with colorblindness can easily see.

Check our detailed guide on how to create a heatmap here. Also discover our collection of heatmap PowerPoint templates .

Pie charts are circular statistical graphics divided into slices to illustrate numerical proportions. Each slice represents a proportionate part of the whole, making it easy to visualize the contribution of each component to the total.

The size of the pie charts is influenced by the value of data points within each pie. The total of all data points in a pie determines its size. The pie with the highest data points appears as the largest, whereas the others are proportionally smaller. However, you can present all pies of the same size if proportional representation is not required [9] . Sometimes, pie charts are difficult to read, or additional information is required. A variation of this tool can be used instead, known as the donut chart , which has the same structure but a blank center, creating a ring shape. Presenters can add extra information, and the ring shape helps to declutter the graph.

Pie charts are used in business to show percentage distribution, compare relative sizes of categories, or present straightforward data sets where visualizing ratios is essential.

Real-Life Application of Pie Charts

Consider a scenario where you want to represent the distribution of the data. Each slice of the pie chart would represent a different category, and the size of each slice would indicate the percentage of the total portion allocated to that category.

Step 1: Define Your Data Structure

Imagine you are presenting the distribution of a project budget among different expense categories.

• Column A: Expense Categories (Personnel, Equipment, Marketing, Miscellaneous)
• Column B: Budget Amounts ($40,000, $30,000, $20,000, $10,000) Column B represents the values of your categories in Column A.

Step 2: Insert a Pie Chart

Using any of the accessible tools, you can create a pie chart. The most convenient tools for forming a pie chart in a presentation are presentation tools such as PowerPoint or Google Slides.  You will notice that the pie chart assigns each expense category a percentage of the total budget by dividing it by the total budget.

For instance:

• Personnel: $40,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 40%
• Equipment: $30,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 30%
• Marketing: $20,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 20%
• Miscellaneous: $10,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 10%

You can make a chart out of this or just pull out the pie chart from the data.

3D pie charts and 3D donut charts are quite popular among the audience. They stand out as visual elements in any presentation slide, so let’s take a look at how our pie chart example would look in 3D pie chart format.

Step 03: Results Interpretation

The pie chart visually illustrates the distribution of the project budget among different expense categories. Personnel constitutes the largest portion at 40%, followed by equipment at 30%, marketing at 20%, and miscellaneous at 10%. This breakdown provides a clear overview of where the project funds are allocated, which helps in informed decision-making and resource management. It is evident that personnel are a significant investment, emphasizing their importance in the overall project budget.

Pie charts provide a straightforward way to represent proportions and percentages. They are easy to understand, even for individuals with limited data analysis experience. These charts work well for small datasets with a limited number of categories.

However, a pie chart can become cluttered and less effective in situations with many categories. Accurate interpretation may be challenging, especially when dealing with slight differences in slice sizes. In addition, these charts are static and do not effectively convey trends over time.

For more information, check our collection of pie chart templates for PowerPoint .

Histograms present the distribution of numerical variables. Unlike a bar chart that records each unique response separately, histograms organize numeric responses into bins and show the frequency of reactions within each bin [10] . The x-axis of a histogram shows the range of values for a numeric variable. At the same time, the y-axis indicates the relative frequencies (percentage of the total counts) for that range of values.

Whenever you want to understand the distribution of your data, check which values are more common, or identify outliers, histograms are your go-to. Think of them as a spotlight on the story your data is telling. A histogram can provide a quick and insightful overview if you’re curious about exam scores, sales figures, or any numerical data distribution.

Real-Life Application of a Histogram

In the histogram data analysis presentation example, imagine an instructor analyzing a class’s grades to identify the most common score range. A histogram could effectively display the distribution. It will show whether most students scored in the average range or if there are significant outliers.

Step 1: Gather Data

He begins by gathering the data. The scores of each student in class are gathered to analyze exam scores.

After arranging the scores in ascending order, bin ranges are set.

Step 2: Define Bins

Bins are like categories that group similar values. Think of them as buckets that organize your data. The presenter decides how wide each bin should be based on the range of the values. For instance, the instructor sets the bin ranges based on score intervals: 60-69, 70-79, 80-89, and 90-100.

Step 3: Count Frequency

Now, he counts how many data points fall into each bin. This step is crucial because it tells you how often specific ranges of values occur. The result is the frequency distribution, showing the occurrences of each group.

Here, the instructor counts the number of students in each category.

• 60-69: 1 student (Kate)
• 70-79: 4 students (David, Emma, Grace, Jack)
• 80-89: 7 students (Alice, Bob, Frank, Isabel, Liam, Mia, Noah)
• 90-100: 3 students (Clara, Henry, Olivia)

Step 4: Create the Histogram

It’s time to turn the data into a visual representation. Draw a bar for each bin on a graph. The width of the bar should correspond to the range of the bin, and the height should correspond to the frequency.  To make your histogram understandable, label the X and Y axes.

In this case, the X-axis should represent the bins (e.g., test score ranges), and the Y-axis represents the frequency.

The histogram of the class grades reveals insightful patterns in the distribution. Most students, with seven students, fall within the 80-89 score range. The histogram provides a clear visualization of the class’s performance. It showcases a concentration of grades in the upper-middle range with few outliers at both ends. This analysis helps in understanding the overall academic standing of the class. It also identifies the areas for potential improvement or recognition.

Thus, histograms provide a clear visual representation of data distribution. They are easy to interpret, even for those without a statistical background. They apply to various types of data, including continuous and discrete variables. One weak point is that histograms do not capture detailed patterns in students’ data, with seven compared to other visualization methods.

A scatter plot is a graphical representation of the relationship between two variables. It consists of individual data points on a two-dimensional plane. This plane plots one variable on the x-axis and the other on the y-axis. Each point represents a unique observation. It visualizes patterns, trends, or correlations between the two variables.

Scatter plots are also effective in revealing the strength and direction of relationships. They identify outliers and assess the overall distribution of data points. The points’ dispersion and clustering reflect the relationship’s nature, whether it is positive, negative, or lacks a discernible pattern. In business, scatter plots assess relationships between variables such as marketing cost and sales revenue. They help present data correlations and decision-making.

Real-Life Application of Scatter Plot

A group of scientists is conducting a study on the relationship between daily hours of screen time and sleep quality. After reviewing the data, they managed to create this table to help them build a scatter plot graph:

In the provided example, the x-axis represents Daily Hours of Screen Time, and the y-axis represents the Sleep Quality Rating.

The scientists observe a negative correlation between the amount of screen time and the quality of sleep. This is consistent with their hypothesis that blue light, especially before bedtime, has a significant impact on sleep quality and metabolic processes.

There are a few things to remember when using a scatter plot. Even when a scatter diagram indicates a relationship, it doesn’t mean one variable affects the other. A third factor can influence both variables. The more the plot resembles a straight line, the stronger the relationship is perceived [11] . If it suggests no ties, the observed pattern might be due to random fluctuations in data. When the scatter diagram depicts no correlation, whether the data might be stratified is worth considering.

Choosing the appropriate data presentation type is crucial when making a presentation . Understanding the nature of your data and the message you intend to convey will guide this selection process. For instance, when showcasing quantitative relationships, scatter plots become instrumental in revealing correlations between variables. If the focus is on emphasizing parts of a whole, pie charts offer a concise display of proportions. Histograms, on the other hand, prove valuable for illustrating distributions and frequency patterns. 

Bar charts provide a clear visual comparison of different categories. Likewise, line charts excel in showcasing trends over time, while tables are ideal for detailed data examination. Starting a presentation on data presentation types involves evaluating the specific information you want to communicate and selecting the format that aligns with your message. This ensures clarity and resonance with your audience from the beginning of your presentation.

1. Fact Sheet Dashboard for Data Presentation

Convey all the data you need to present in this one-pager format, an ideal solution tailored for users looking for presentation aids. Global maps, donut chats, column graphs, and text neatly arranged in a clean layout presented in light and dark themes.

Use This Template

2. 3D Column Chart Infographic PPT Template

Represent column charts in a highly visual 3D format with this PPT template. A creative way to present data, this template is entirely editable, and we can craft either a one-page infographic or a series of slides explaining what we intend to disclose point by point.

3. Data Circles Infographic PowerPoint Template

An alternative to the pie chart and donut chart diagrams, this template features a series of curved shapes with bubble callouts as ways of presenting data. Expand the information for each arch in the text placeholder areas.

4. Colorful Metrics Dashboard for Data Presentation

This versatile dashboard template helps us in the presentation of the data by offering several graphs and methods to convert numbers into graphics. Implement it for e-commerce projects, financial projections, project development, and more.

5. Animated Data Presentation Tools for PowerPoint & Google Slides

A slide deck filled with most of the tools mentioned in this article, from bar charts, column charts, treemap graphs, pie charts, histogram, etc. Animated effects make each slide look dynamic when sharing data with stakeholders.

6. Statistics Waffle Charts PPT Template for Data Presentations

This PPT template helps us how to present data beyond the typical pie chart representation. It is widely used for demographics, so it’s a great fit for marketing teams, data science professionals, HR personnel, and more.

7. Data Presentation Dashboard Template for Google Slides

A compendium of tools in dashboard format featuring line graphs, bar charts, column charts, and neatly arranged placeholder text areas. 

8. Weather Dashboard for Data Presentation

Share weather data for agricultural presentation topics, environmental studies, or any kind of presentation that requires a highly visual layout for weather forecasting on a single day. Two color themes are available.

9. Social Media Marketing Dashboard Data Presentation Template

Intended for marketing professionals, this dashboard template for data presentation is a tool for presenting data analytics from social media channels. Two slide layouts featuring line graphs and column charts.

10. Project Management Summary Dashboard Template

A tool crafted for project managers to deliver highly visual reports on a project’s completion, the profits it delivered for the company, and expenses/time required to execute it. 4 different color layouts are available.

11. Profit & Loss Dashboard for PowerPoint and Google Slides

A must-have for finance professionals. This typical profit & loss dashboard includes progress bars, donut charts, column charts, line graphs, and everything that’s required to deliver a comprehensive report about a company’s financial situation.

Overwhelming visuals

One of the mistakes related to using data-presenting methods is including too much data or using overly complex visualizations. They can confuse the audience and dilute the key message.

Inappropriate chart types

Choosing the wrong type of chart for the data at hand can lead to misinterpretation. For example, using a pie chart for data that doesn’t represent parts of a whole is not right.

Lack of context

Failing to provide context or sufficient labeling can make it challenging for the audience to understand the significance of the presented data.

Inconsistency in design

Using inconsistent design elements and color schemes across different visualizations can create confusion and visual disarray.

Failure to provide details

Simply presenting raw data without offering clear insights or takeaways can leave the audience without a meaningful conclusion.

Lack of focus

Not having a clear focus on the key message or main takeaway can result in a presentation that lacks a central theme.

Visual accessibility issues

Overlooking the visual accessibility of charts and graphs can exclude certain audience members who may have difficulty interpreting visual information.

In order to avoid these mistakes in data presentation, presenters can benefit from using presentation templates . These templates provide a structured framework. They ensure consistency, clarity, and an aesthetically pleasing design, enhancing data communication’s overall impact.

Understanding and choosing data presentation types are pivotal in effective communication. Each method serves a unique purpose, so selecting the appropriate one depends on the nature of the data and the message to be conveyed. The diverse array of presentation types offers versatility in visually representing information, from bar charts showing values to pie charts illustrating proportions. 

Using the proper method enhances clarity, engages the audience, and ensures that data sets are not just presented but comprehensively understood. By appreciating the strengths and limitations of different presentation types, communicators can tailor their approach to convey information accurately, developing a deeper connection between data and audience understanding.

[1] Government of Canada, S.C. (2021) 5 Data Visualization 5.2 Bar Chart , 5.2 Bar chart .  https://www150.statcan.gc.ca/n1/edu/power-pouvoir/ch9/bargraph-diagrammeabarres/5214818-eng.htm

[2] Kosslyn, S.M., 1989. Understanding charts and graphs. Applied cognitive psychology, 3(3), pp.185-225. https://apps.dtic.mil/sti/pdfs/ADA183409.pdf

[3] Creating a Dashboard . https://it.tufts.edu/book/export/html/1870

[4] https://www.goldenwestcollege.edu/research/data-and-more/data-dashboards/index.html

[5] https://www.mit.edu/course/21/21.guide/grf-line.htm

[6] Jadeja, M. and Shah, K., 2015, January. Tree-Map: A Visualization Tool for Large Data. In GSB@ SIGIR (pp. 9-13). https://ceur-ws.org/Vol-1393/gsb15proceedings.pdf#page=15

[7] Heat Maps and Quilt Plots. https://www.publichealth.columbia.edu/research/population-health-methods/heat-maps-and-quilt-plots

[8] EIU QGIS WORKSHOP. https://www.eiu.edu/qgisworkshop/heatmaps.php

[9] About Pie Charts.  https://www.mit.edu/~mbarker/formula1/f1help/11-ch-c8.htm

[10] Histograms. https://sites.utexas.edu/sos/guided/descriptive/numericaldd/descriptiven2/histogram/ [11] https://asq.org/quality-resources/scatter-diagram

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It is the simplest form of data Presentation often used in schools or universities to provide a clearer picture to students, who are better able to capture the concepts effectively through a pictorial Presentation of simple data.

2. Column chart

It is a simplified version of the pictorial Presentation which involves the management of a larger amount of data being shared during the presentations and providing suitable clarity to the insights of the data.

3. Pie Charts

Pie charts provide a very descriptive & a 2D depiction of the data pertaining to comparisons or resemblance of data in two separate fields.

4. Bar charts

A bar chart that shows the accumulation of data with cuboid bars with different dimensions & lengths which are directly proportionate to the values they represent. The bars can be placed either vertically or horizontally depending on the data being represented.

5. Histograms

It is a perfect Presentation of the spread of numerical data. The main differentiation that separates data graphs and histograms are the gaps in the data graphs.

6. Box plots

Box plot or Box-plot is a way of representing groups of numerical data through quartiles. Data Presentation is easier with this style of graph dealing with the extraction of data to the minutes of difference.

Map Data graphs help you with data Presentation over an area to display the areas of concern. Map graphs are useful to make an exact depiction of data over a vast case scenario.

All these visual presentations share a common goal of creating meaningful insights and a platform to understand and manage the data in relation to the growth and expansion of one’s in-depth understanding of data & details to plan or execute future decisions or actions.

Importance of Data Presentation

Data Presentation could be both can be a deal maker or deal breaker based on the delivery of the content in the context of visual depiction.

Data Presentation tools are powerful communication tools that can simplify the data by making it easily understandable & readable at the same time while attracting & keeping the interest of its readers and effectively showcase large amounts of complex data in a simplified manner.

If the user can create an insightful presentation of the data in hand with the same sets of facts and figures, then the results promise to be impressive.

There have been situations where the user has had a great amount of data and vision for expansion but the presentation drowned his/her vision.

To impress the higher management and top brass of a firm, effective presentation of data is needed.

Data Presentation helps the clients or the audience to not spend time grasping the concept and the future alternatives of the business and to convince them to invest in the company & turn it profitable both for the investors & the company.

Although data presentation has a lot to offer, the following are some of the major reason behind the essence of an effective presentation:-

• Many consumers or higher authorities are interested in the interpretation of data, not the raw data itself. Therefore, after the analysis of the data, users should represent the data with a visual aspect for better understanding and knowledge.
• The user should not overwhelm the audience with a number of slides of the presentation and inject an ample amount of texts as pictures that will speak for themselves.
• Data presentation often happens in a nutshell with each department showcasing their achievements towards company growth through a graph or a histogram.
• Providing a brief description would help the user to attain attention in a small amount of time while informing the audience about the context of the presentation
• The inclusion of pictures, charts, graphs and tables in the presentation help for better understanding the potential outcomes.
• An effective presentation would allow the organization to determine the difference with the fellow organization and acknowledge its flaws. Comparison of data would assist them in decision making.

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Data presentation: A comprehensive guide

Learn how to create data presentation effectively and communicate your insights in a way that is clear, concise, and engaging.

Raja Bothra

Building presentations

Hey there, fellow data enthusiast!

Welcome to our comprehensive guide on data presentation.

Whether you're an experienced presenter or just starting, this guide will help you present your data like a pro. We'll dive deep into what data presentation is, why it's crucial, and how to master it. So, let's embark on this data-driven journey together.

What is data presentation?

Data presentation is the art of transforming raw data into a visual format that's easy to understand and interpret. It's like turning numbers and statistics into a captivating story that your audience can quickly grasp. When done right, data presentation can be a game-changer, enabling you to convey complex information effectively.

Why are data presentations important?

Imagine drowning in a sea of numbers and figures. That's how your audience might feel without proper data presentation. Here's why it's essential:

• Clarity : Data presentations make complex information clear and concise.
• Engagement : Visuals, such as charts and graphs, grab your audience's attention.
• Comprehension : Visual data is easier to understand than long, numerical reports.
• Decision-making : Well-presented data aids informed decision-making.
• Impact : It leaves a lasting impression on your audience.

Types of data presentation:

Now, let's delve into the diverse array of data presentation methods, each with its own unique strengths and applications. We have three primary types of data presentation, and within these categories, numerous specific visualization techniques can be employed to effectively convey your data.

1. Textual presentation

Textual presentation harnesses the power of words and sentences to elucidate and contextualize your data. This method is commonly used to provide a narrative framework for the data, offering explanations, insights, and the broader implications of your findings. It serves as a foundation for a deeper understanding of the data's significance.

2. Tabular presentation

Tabular presentation employs tables to arrange and structure your data systematically. These tables are invaluable for comparing various data groups or illustrating how data evolves over time. They present information in a neat and organized format, facilitating straightforward comparisons and reference points.

3. Graphical presentation

Graphical presentation harnesses the visual impact of charts and graphs to breathe life into your data. Charts and graphs are powerful tools for spotlighting trends, patterns, and relationships hidden within the data. Let's explore some common graphical presentation methods:

• Bar charts: They are ideal for comparing different categories of data. In this method, each category is represented by a distinct bar, and the height of the bar corresponds to the value it represents. Bar charts provide a clear and intuitive way to discern differences between categories.
• Pie charts: It excel at illustrating the relative proportions of different data categories. Each category is depicted as a slice of the pie, with the size of each slice corresponding to the percentage of the total value it represents. Pie charts are particularly effective for showcasing the distribution of data.
• Line graphs: They are the go-to choice when showcasing how data evolves over time. Each point on the line represents a specific value at a particular time period. This method enables viewers to track trends and fluctuations effortlessly, making it perfect for visualizing data with temporal dimensions.
• Scatter plots: They are the tool of choice when exploring the relationship between two variables. In this method, each point on the plot represents a pair of values for the two variables in question. Scatter plots help identify correlations, outliers, and patterns within data pairs.

The selection of the most suitable data presentation method hinges on the specific dataset and the presentation's objectives. For instance, when comparing sales figures of different products, a bar chart shines in its simplicity and clarity. On the other hand, if your aim is to display how a product's sales have changed over time, a line graph provides the ideal visual narrative.

Additionally, it's crucial to factor in your audience's level of familiarity with data presentations. For a technical audience, more intricate visualization methods may be appropriate. However, when presenting to a general audience, opting for straightforward and easily understandable visuals is often the wisest choice.

In the world of data presentation, choosing the right method is akin to selecting the perfect brush for a masterpiece. Each tool has its place, and understanding when and how to use them is key to crafting compelling and insightful presentations. So, consider your data carefully, align your purpose, and paint a vivid picture that resonates with your audience.

What to include in data presentation?

When creating your data presentation, remember these key components:

• Data points : Clearly state the data points you're presenting.
• Comparison : Highlight comparisons and trends in your data.
• Graphical methods : Choose the right chart or graph for your data.
• Infographics : Use visuals like infographics to make information more digestible.
• Numerical values : Include numerical values to support your visuals.
• Qualitative information : Explain the significance of the data.
• Source citation : Always cite your data sources.

How to structure an effective data presentation?

Creating a well-structured data presentation is not just important; it's the backbone of a successful presentation. Here's a step-by-step guide to help you craft a compelling and organized presentation that captivates your audience:

1. Know your audience

Understanding your audience is paramount. Consider their needs, interests, and existing knowledge about your topic. Tailor your presentation to their level of understanding, ensuring that it resonates with them on a personal level. Relevance is the key.

2. Have a clear message

Every effective data presentation should convey a clear and concise message. Determine what you want your audience to learn or take away from your presentation, and make sure your message is the guiding light throughout your presentation. Ensure that all your data points align with and support this central message.

3. Tell a compelling story

Human beings are naturally wired to remember stories. Incorporate storytelling techniques into your presentation to make your data more relatable and memorable. Your data can be the backbone of a captivating narrative, whether it's about a trend, a problem, or a solution. Take your audience on a journey through your data.

4. Leverage visuals

Visuals are a powerful tool in data presentation. They make complex information accessible and engaging. Utilize charts, graphs, and images to illustrate your points and enhance the visual appeal of your presentation. Visuals should not just be an accessory; they should be an integral part of your storytelling.

5. Be clear and concise

Avoid jargon or technical language that your audience may not comprehend. Use plain language and explain your data points clearly. Remember, clarity is king. Each piece of information should be easy for your audience to digest.

6. Practice your delivery

Practice makes perfect. Rehearse your presentation multiple times before the actual delivery. This will help you deliver it smoothly and confidently, reducing the chances of stumbling over your words or losing track of your message.

A basic structure for an effective data presentation

Armed with a comprehensive comprehension of how to construct a compelling data presentation, you can now utilize this fundamental template for guidance:

In the introduction, initiate your presentation by introducing both yourself and the topic at hand. Clearly articulate your main message or the fundamental concept you intend to communicate.

Moving on to the body of your presentation, organize your data in a coherent and easily understandable sequence. Employ visuals generously to elucidate your points and weave a narrative that enhances the overall story. Ensure that the arrangement of your data aligns with and reinforces your central message.

As you approach the conclusion, succinctly recapitulate your key points and emphasize your core message once more. Conclude by leaving your audience with a distinct and memorable takeaway, ensuring that your presentation has a lasting impact.

Additional tips for enhancing your data presentation

To take your data presentation to the next level, consider these additional tips:

• Consistent design : Maintain a uniform design throughout your presentation. This not only enhances visual appeal but also aids in seamless comprehension.
• High-quality visuals : Ensure that your visuals are of high quality, easy to read, and directly relevant to your topic.
• Concise text : Avoid overwhelming your slides with excessive text. Focus on the most critical points, using visuals to support and elaborate.
• Anticipate questions : Think ahead about the questions your audience might pose. Be prepared with well-thought-out answers to foster productive discussions.

By following these guidelines, you can structure an effective data presentation that not only informs but also engages and inspires your audience. Remember, a well-structured presentation is the bridge that connects your data to your audience's understanding and appreciation.

Do’s and don'ts on a data presentation

• Use visuals : Incorporate charts and graphs to enhance understanding.
• Keep it simple : Avoid clutter and complexity.
• Highlight key points : Emphasize crucial data.
• Engage the audience : Encourage questions and discussions.
• Practice : Rehearse your presentation.

Don'ts:

• Overload with data : Less is often more; don't overwhelm your audience.
• Fit Unrelated data : Stay on topic; don't include irrelevant information.
• Neglect the audience : Ensure your presentation suits your audience's level of expertise.
• Read word-for-word : Avoid reading directly from slides.
• Lose focus : Stick to your presentation's purpose.

Summarizing key takeaways

• Definition : Data presentation is the art of visualizing complex data for better understanding.
• Importance : Data presentations enhance clarity, engage the audience, aid decision-making, and leave a lasting impact.
• Types : Textual, Tabular, and Graphical presentations offer various ways to present data.
• Choosing methods : Select the right method based on data, audience, and purpose.
• Components : Include data points, comparisons, visuals, infographics, numerical values, and source citations.
• Structure : Know your audience, have a clear message, tell a compelling story, use visuals, be concise, and practice.
• Do's and don'ts : Do use visuals, keep it simple, highlight key points, engage the audience, and practice. Don't overload with data, include unrelated information, neglect the audience's expertise, read word-for-word, or lose focus.

1. What is data presentation, and why is it important in 2023?

Data presentation is the process of visually representing data sets to convey information effectively to an audience. In an era where the amount of data generated is vast, visually presenting data using methods such as diagrams, graphs, and charts has become crucial. By simplifying complex data sets, presentation of the data may helps your audience quickly grasp much information without drowning in a sea of chart's, analytics, facts and figures.

2. What are some common methods of data presentation?

There are various methods of data presentation, including graphs and charts, histograms, and cumulative frequency polygons. Each method has its strengths and is often used depending on the type of data you're using and the message you want to convey. For instance, if you want to show data over time, try using a line graph. If you're presenting geographical data, consider to use a heat map.

3. How can I ensure that my data presentation is clear and readable?

To ensure that your data presentation is clear and readable, pay attention to the design and labeling of your charts. Don't forget to label the axes appropriately, as they are critical for understanding the values they represent. Don't fit all the information in one slide or in a single paragraph. Presentation software like Prezent and PowerPoint can help you simplify your vertical axis, charts and tables, making them much easier to understand.

4. What are some common mistakes presenters make when presenting data?

One common mistake is trying to fit too much data into a single chart, which can distort the information and confuse the audience. Another mistake is not considering the needs of the audience. Remember that your audience won't have the same level of familiarity with the data as you do, so it's essential to present the data effectively and respond to questions during a Q&A session.

5. How can I use data visualization to present important data effectively on platforms like LinkedIn?

When presenting data on platforms like LinkedIn, consider using eye-catching visuals like bar graphs or charts. Use concise captions and e.g., examples to highlight the single most important information in your data report. Visuals, such as graphs and tables, can help you stand out in the sea of textual content, making your data presentation more engaging and shareable among your LinkedIn connections.

Create your data presentation with prezent

Prezent can be a valuable tool for creating data presentations. Here's how Prezent can help you in this regard:

• Time savings : Prezent saves up to 70% of presentation creation time, allowing you to focus on data analysis and insights.
• On-brand consistency : Ensure 100% brand alignment with Prezent's brand-approved designs for professional-looking data presentations.
• Effortless collaboration : Real-time sharing and collaboration features make it easy for teams to work together on data presentations.
• Data storytelling : Choose from 50+ storylines to effectively communicate data insights and engage your audience.
• Personalization : Create tailored data presentations that resonate with your audience's preferences, enhancing the impact of your data.

In summary, Prezent streamlines the process of creating data presentations by offering time-saving features, ensuring brand consistency, promoting collaboration, and providing tools for effective data storytelling. Whether you need to present data to clients, stakeholders, or within your organization, Prezent can significantly enhance your presentation-making process.

So, go ahead, present your data with confidence, and watch your audience be wowed by your expertise.

Thank you for joining us on this data-driven journey. Stay tuned for more insights, and remember, data presentation is your ticket to making numbers come alive!

Sign up for our free trial or book a demo ! ‍

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Blog Data Visualization 10 Data Presentation Examples For Strategic Communication

10 Data Presentation Examples For Strategic Communication

Written by: Krystle Wong Sep 28, 2023

Knowing how to present data is like having a superpower. 

Data presentation today is no longer just about numbers on a screen; it’s storytelling with a purpose. It’s about captivating your audience, making complex stuff look simple and inspiring action. 

To help turn your data into stories that stick, influence decisions and make an impact, check out Venngage’s free chart maker or follow me on a tour into the world of data storytelling along with data presentation templates that work across different fields, from business boardrooms to the classroom and beyond. Keep scrolling to learn more! 

Click to jump ahead:

10 Essential data presentation examples + methods you should know

What should be included in a data presentation, what are some common mistakes to avoid when presenting data, faqs on data presentation examples, transform your message with impactful data storytelling.

Data presentation is a vital skill in today’s information-driven world. Whether you’re in business, academia, or simply want to convey information effectively, knowing the different ways of presenting data is crucial. For impactful data storytelling, consider these essential data presentation methods:

1. Bar graph

Ideal for comparing data across categories or showing trends over time.

Bar graphs, also known as bar charts are workhorses of data presentation. They’re like the Swiss Army knives of visualization methods because they can be used to compare data in different categories or display data changes over time. 

In a bar chart, categories are displayed on the x-axis and the corresponding values are represented by the height of the bars on the y-axis. 

It’s a straightforward and effective way to showcase raw data, making it a staple in business reports, academic presentations and beyond.

Make sure your bar charts are concise with easy-to-read labels. Whether your bars go up or sideways, keep it simple by not overloading with too many categories.

2. Line graph

Great for displaying trends and variations in data points over time or continuous variables.

Line charts or line graphs are your go-to when you want to visualize trends and variations in data sets over time.

One of the best quantitative data presentation examples, they work exceptionally well for showing continuous data, such as sales projections over the last couple of years or supply and demand fluctuations. 

The x-axis represents time or a continuous variable and the y-axis represents the data values. By connecting the data points with lines, you can easily spot trends and fluctuations.

A tip when presenting data with line charts is to minimize the lines and not make it too crowded. Highlight the big changes, put on some labels and give it a catchy title.

3. Pie chart

Useful for illustrating parts of a whole, such as percentages or proportions.

Pie charts are perfect for showing how a whole is divided into parts. They’re commonly used to represent percentages or proportions and are great for presenting survey results that involve demographic data. 

Each “slice” of the pie represents a portion of the whole and the size of each slice corresponds to its share of the total. 

While pie charts are handy for illustrating simple distributions, they can become confusing when dealing with too many categories or when the differences in proportions are subtle.

Don’t get too carried away with slices — label those slices with percentages or values so people know what’s what and consider using a legend for more categories.

4. Scatter plot

Effective for showing the relationship between two variables and identifying correlations.

Scatter plots are all about exploring relationships between two variables. They’re great for uncovering correlations, trends or patterns in data. 

In a scatter plot, every data point appears as a dot on the chart, with one variable marked on the horizontal x-axis and the other on the vertical y-axis.

By examining the scatter of points, you can discern the nature of the relationship between the variables, whether it’s positive, negative or no correlation at all.

If you’re using scatter plots to reveal relationships between two variables, be sure to add trendlines or regression analysis when appropriate to clarify patterns. Label data points selectively or provide tooltips for detailed information.

5. Histogram

Best for visualizing the distribution and frequency of a single variable.

Histograms are your choice when you want to understand the distribution and frequency of a single variable. 

They divide the data into “bins” or intervals and the height of each bar represents the frequency or count of data points falling into that interval. 

Histograms are excellent for helping to identify trends in data distributions, such as peaks, gaps or skewness.

Here’s something to take note of — ensure that your histogram bins are appropriately sized to capture meaningful data patterns. Using clear axis labels and titles can also help explain the distribution of the data effectively.

6. Stacked bar chart

Useful for showing how different components contribute to a whole over multiple categories.

Stacked bar charts are a handy choice when you want to illustrate how different components contribute to a whole across multiple categories. 

Each bar represents a category and the bars are divided into segments to show the contribution of various components within each category. 

This method is ideal for highlighting both the individual and collective significance of each component, making it a valuable tool for comparative analysis.

Stacked bar charts are like data sandwiches—label each layer so people know what’s what. Keep the order logical and don’t forget the paintbrush for snazzy colors. Here’s a data analysis presentation example on writers’ productivity using stacked bar charts:

7. Area chart

Similar to line charts but with the area below the lines filled, making them suitable for showing cumulative data.

Area charts are close cousins of line charts but come with a twist. 

Imagine plotting the sales of a product over several months. In an area chart, the space between the line and the x-axis is filled, providing a visual representation of the cumulative total. 

This makes it easy to see how values stack up over time, making area charts a valuable tool for tracking trends in data.

For area charts, use them to visualize cumulative data and trends, but avoid overcrowding the chart. Add labels, especially at significant points and make sure the area under the lines is filled with a visually appealing color gradient.

8. Tabular presentation

Presenting data in rows and columns, often used for precise data values and comparisons.

Tabular data presentation is all about clarity and precision. Think of it as presenting numerical data in a structured grid, with rows and columns clearly displaying individual data points. 

A table is invaluable for showcasing detailed data, facilitating comparisons and presenting numerical information that needs to be exact. They’re commonly used in reports, spreadsheets and academic papers.

When presenting tabular data, organize it neatly with clear headers and appropriate column widths. Highlight important data points or patterns using shading or font formatting for better readability.

9. Textual data

Utilizing written or descriptive content to explain or complement data, such as annotations or explanatory text.

Textual data presentation may not involve charts or graphs, but it’s one of the most used qualitative data presentation examples. 

It involves using written content to provide context, explanations or annotations alongside data visuals. Think of it as the narrative that guides your audience through the data. 

Well-crafted textual data can make complex information more accessible and help your audience understand the significance of the numbers and visuals.

Textual data is your chance to tell a story. Break down complex information into bullet points or short paragraphs and use headings to guide the reader’s attention.

10. Pictogram

Using simple icons or images to represent data is especially useful for conveying information in a visually intuitive manner.

Pictograms are all about harnessing the power of images to convey data in an easy-to-understand way. 

Instead of using numbers or complex graphs, you use simple icons or images to represent data points. 

For instance, you could use a thumbs up emoji to illustrate customer satisfaction levels, where each face represents a different level of satisfaction. 

Pictograms are great for conveying data visually, so choose symbols that are easy to interpret and relevant to the data. Use consistent scaling and a legend to explain the symbols’ meanings, ensuring clarity in your presentation.

Looking for more data presentation ideas? Use the Venngage graph maker or browse through our gallery of chart templates to pick a template and get started! 

A comprehensive data presentation should include several key elements to effectively convey information and insights to your audience. Here’s a list of what should be included in a data presentation:

1. Title and objective

• Begin with a clear and informative title that sets the context for your presentation.
• State the primary objective or purpose of the presentation to provide a clear focus.

2. Key data points

• Present the most essential data points or findings that align with your objective.
• Use charts, graphical presentations or visuals to illustrate these key points for better comprehension.

3. Context and significance

• Provide a brief overview of the context in which the data was collected and why it’s significant.
• Explain how the data relates to the larger picture or the problem you’re addressing.

4. Key takeaways

• Summarize the main insights or conclusions that can be drawn from the data.
• Highlight the key takeaways that the audience should remember.

5. Visuals and charts

• Use clear and appropriate visual aids to complement the data.
• Ensure that visuals are easy to understand and support your narrative.

6. Implications or actions

• Discuss the practical implications of the data or any recommended actions.
• If applicable, outline next steps or decisions that should be taken based on the data.

7. Q&A and discussion

• Allocate time for questions and open discussion to engage the audience.
• Address queries and provide additional insights or context as needed.

Presenting data is a crucial skill in various professional fields, from business to academia and beyond. To ensure your data presentations hit the mark, here are some common mistakes that you should steer clear of:

Overloading with data

Presenting too much data at once can overwhelm your audience. Focus on the key points and relevant information to keep the presentation concise and focused. Here are some free data visualization tools you can use to convey data in an engaging and impactful way. 

Assuming everyone’s on the same page

It’s easy to assume that your audience understands as much about the topic as you do. But this can lead to either dumbing things down too much or diving into a bunch of jargon that leaves folks scratching their heads. Take a beat to figure out where your audience is coming from and tailor your presentation accordingly.

Misleading visuals

Using misleading visuals, such as distorted scales or inappropriate chart types can distort the data’s meaning. Pick the right data infographics and understandable charts to ensure that your visual representations accurately reflect the data.

Not providing context

Data without context is like a puzzle piece with no picture on it. Without proper context, data may be meaningless or misinterpreted. Explain the background, methodology and significance of the data.

Not citing sources properly

Neglecting to cite sources and provide citations for your data can erode its credibility. Always attribute data to its source and utilize reliable sources for your presentation.

Not telling a story

Avoid simply presenting numbers. If your presentation lacks a clear, engaging story that takes your audience on a journey from the beginning (setting the scene) through the middle (data analysis) to the end (the big insights and recommendations), you’re likely to lose their interest.

Infographics are great for storytelling because they mix cool visuals with short and sweet text to explain complicated stuff in a fun and easy way. Create one with Venngage’s free infographic maker to create a memorable story that your audience will remember.

Ignoring data quality

Presenting data without first checking its quality and accuracy can lead to misinformation. Validate and clean your data before presenting it.

Simplify your visuals

Fancy charts might look cool, but if they confuse people, what’s the point? Go for the simplest visual that gets your message across. Having a dilemma between presenting data with infographics v.s data design? This article on the difference between data design and infographics might help you out. 

Missing the emotional connection

Data isn’t just about numbers; it’s about people and real-life situations. Don’t forget to sprinkle in some human touch, whether it’s through relatable stories, examples or showing how the data impacts real lives.

Skipping the actionable insights

At the end of the day, your audience wants to know what they should do with all the data. If you don’t wrap up with clear, actionable insights or recommendations, you’re leaving them hanging. Always finish up with practical takeaways and the next steps.

Can you provide some data presentation examples for business reports?

Business reports often benefit from data presentation through bar charts showing sales trends over time, pie charts displaying market share,or tables presenting financial performance metrics like revenue and profit margins.

What are some creative data presentation examples for academic presentations?

Creative data presentation ideas for academic presentations include using statistical infographics to illustrate research findings and statistical data, incorporating storytelling techniques to engage the audience or utilizing heat maps to visualize data patterns.

What are the key considerations when choosing the right data presentation format?

When choosing a chart format , consider factors like data complexity, audience expertise and the message you want to convey. Options include charts (e.g., bar, line, pie), tables, heat maps, data visualization infographics and interactive dashboards.

Knowing the type of data visualization that best serves your data is just half the battle. Here are some best practices for data visualization to make sure that the final output is optimized. 

How can I choose the right data presentation method for my data?

To select the right data presentation method, start by defining your presentation’s purpose and audience. Then, match your data type (e.g., quantitative, qualitative) with suitable visualization techniques (e.g., histograms, word clouds) and choose an appropriate presentation format (e.g., slide deck, report, live demo).

For more presentation ideas , check out this guide on how to make a good presentation or use a presentation software to simplify the process.  

How can I make my data presentations more engaging and informative?

To enhance data presentations, use compelling narratives, relatable examples and fun data infographics that simplify complex data. Encourage audience interaction, offer actionable insights and incorporate storytelling elements to engage and inform effectively.

The opening of your presentation holds immense power in setting the stage for your audience. To design a presentation and convey your data in an engaging and informative, try out Venngage’s free presentation maker to pick the right presentation design for your audience and topic. 

What is the difference between data visualization and data presentation?

Data presentation typically involves conveying data reports and insights to an audience, often using visuals like charts and graphs. Data visualization , on the other hand, focuses on creating those visual representations of data to facilitate understanding and analysis. 

Now that you’ve learned a thing or two about how to use these methods of data presentation to tell a compelling data story , it’s time to take these strategies and make them your own. 

But here’s the deal: these aren’t just one-size-fits-all solutions. Remember that each example we’ve uncovered here is not a rigid template but a source of inspiration. It’s all about making your audience go, “Wow, I get it now!”

Think of your data presentations as your canvas – it’s where you paint your story, convey meaningful insights and make real change happen. 

So, go forth, present your data with confidence and purpose and watch as your strategic influence grows, one compelling presentation at a time.

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10 Methods of Data Presentation with 5 Great Tips to Practice, Best in 2024

Leah Nguyen • 05 April, 2024 • 17 min read

There are different ways of presenting data, so which one is suited you the most? You can end deathly boring and ineffective data presentation right now with our 10 methods of data presentation . Check out the examples from each technique!

Have you ever presented a data report to your boss/coworkers/teachers thinking it was super dope like you’re some cyber hacker living in the Matrix, but all they saw was a pile of static numbers that seemed pointless and didn’t make sense to them?

Understanding digits is rigid . Making people from non-analytical backgrounds understand those digits is even more challenging.

How can you clear up those confusing numbers in the types of presentation that have the flawless clarity of a diamond? So, let’s check out best way to present data. 💎

Table of Contents

• What are Methods of Data Presentations?
• #1 – Tabular

#3 – Pie chart

#4 – bar chart, #5 – histogram, #6 – line graph, #7 – pictogram graph, #8 – radar chart, #9 – heat map, #10 – scatter plot.

• 5 Mistakes to Avoid
• Best Method of Data Presentation

Frequently Asked Questions

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What are Methods of Data Presentation?

The term ’data presentation’ relates to the way you present data in a way that makes even the most clueless person in the room understand. 

Some say it’s witchcraft (you’re manipulating the numbers in some ways), but we’ll just say it’s the power of turning dry, hard numbers or digits into a visual showcase that is easy for people to digest.

Presenting data correctly can help your audience understand complicated processes, identify trends, and instantly pinpoint whatever is going on without exhausting their brains.

Good data presentation helps…

• Make informed decisions and arrive at positive outcomes . If you see the sales of your product steadily increase throughout the years, it’s best to keep milking it or start turning it into a bunch of spin-offs (shoutout to Star Wars👀).
• Reduce the time spent processing data . Humans can digest information graphically 60,000 times faster than in the form of text. Grant them the power of skimming through a decade of data in minutes with some extra spicy graphs and charts.
• Communicate the results clearly . Data does not lie. They’re based on factual evidence and therefore if anyone keeps whining that you might be wrong, slap them with some hard data to keep their mouths shut.
• Add to or expand the current research . You can see what areas need improvement, as well as what details often go unnoticed while surfing through those little lines, dots or icons that appear on the data board.

Methods of Data Presentation and Examples

Imagine you have a delicious pepperoni, extra-cheese pizza. You can decide to cut it into the classic 8 triangle slices, the party style 12 square slices, or get creative and abstract on those slices. 

There are various ways for cutting a pizza and you get the same variety with how you present your data. In this section, we will bring you the 10 ways to slice a pizza – we mean to present your data – that will make your company’s most important asset as clear as day. Let’s dive into 10 ways to present data efficiently.

#1 – Tabular 

Among various types of data presentation, tabular is the most fundamental method, with data presented in rows and columns. Excel or Google Sheets would qualify for the job. Nothing fancy.

This is an example of a tabular presentation of data on Google Sheets. Each row and column has an attribute (year, region, revenue, etc.), and you can do a custom format to see the change in revenue throughout the year.

When presenting data as text, all you do is write your findings down in paragraphs and bullet points, and that’s it. A piece of cake to you, a tough nut to crack for whoever has to go through all of the reading to get to the point.

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All the above quotes present statistical information in textual form. Since not many people like going through a wall of texts, you’ll have to figure out another route when deciding to use this method, such as breaking the data down into short, clear statements, or even as catchy puns if you’ve got the time to think of them.

A pie chart (or a ‘donut chart’ if you stick a hole in the middle of it) is a circle divided into slices that show the relative sizes of data within a whole. If you’re using it to show percentages, make sure all the slices add up to 100%.

The pie chart is a familiar face at every party and is usually recognised by most people. However, one setback of using this method is our eyes sometimes can’t identify the differences in slices of a circle, and it’s nearly impossible to compare similar slices from two different pie charts, making them the villains in the eyes of data analysts.

Bonus example: A literal ‘pie’ chart! 🥧

The bar chart is a chart that presents a bunch of items from the same category, usually in the form of rectangular bars that are placed at an equal distance from each other. Their heights or lengths depict the values they represent.

They can be as simple as this:

Or more complex and detailed like this example of presentation of data. Contributing to an effective statistic presentation, this one is a grouped bar chart that not only allows you to compare categories but also the groups within them as well.

Similar in appearance to the bar chart but the rectangular bars in histograms don’t often have the gap like their counterparts.

Instead of measuring categories like weather preferences or favourite films as a bar chart does, a histogram only measures things that can be put into numbers.

Teachers can use presentation graphs like a histogram to see which score group most of the students fall into, like in this example above.

Recordings to ways of displaying data, we shouldn’t overlook the effectiveness of line graphs. Line graphs are represented by a group of data points joined together by a straight line. There can be one or more lines to compare how several related things change over time. 

On a line chart’s horizontal axis, you usually have text labels, dates or years, while the vertical axis usually represents the quantity (e.g.: budget, temperature or percentage).

A pictogram graph uses pictures or icons relating to the main topic to visualise a small dataset. The fun combination of colours and illustrations makes it a frequent use at schools.

Pictograms are a breath of fresh air if you want to stay away from the monotonous line chart or bar chart for a while. However, they can present a very limited amount of data and sometimes they are only there for displays and do not represent real statistics.

If presenting five or more variables in the form of a bar chart is too stuffy then you should try using a radar chart, which is one of the most creative ways to present data.

Radar charts show data in terms of how they compare to each other starting from the same point. Some also call them ‘spider charts’ because each aspect combined looks like a spider web.

Radar charts can be a great use for parents who’d like to compare their child’s grades with their peers to lower their self-esteem. You can see that each angular represents a subject with a score value ranging from 0 to 100. Each student’s score across 5 subjects is highlighted in a different colour.

If you think that this method of data presentation somehow feels familiar, then you’ve probably encountered one while playing Pokémon .

A heat map represents data density in colours. The bigger the number, the more colour intense that data will be represented.

Most U.S citizens would be familiar with this data presentation method in geography. For elections, many news outlets assign a specific colour code to a state, with blue representing one candidate and red representing the other. The shade of either blue or red in each state shows the strength of the overall vote in that state.

Another great thing you can use a heat map for is to map what visitors to your site click on. The more a particular section is clicked the ‘hotter’ the colour will turn, from blue to bright yellow to red.

If you present your data in dots instead of chunky bars, you’ll have a scatter plot. 

A scatter plot is a grid with several inputs showing the relationship between two variables. It’s good at collecting seemingly random data and revealing some telling trends.

For example, in this graph, each dot shows the average daily temperature versus the number of beach visitors across several days. You can see that the dots get higher as the temperature increases, so it’s likely that hotter weather leads to more visitors.

5 Data Presentation Mistakes to Avoid

#1 – assume your audience understands what the numbers represent.

You may know all the behind-the-scenes of your data since you’ve worked with them for weeks, but your audience doesn’t.

Showing without telling only invites more and more questions from your audience, as they have to constantly make sense of your data, wasting the time of both sides as a result.

While showing your data presentations, you should tell them what the data are about before hitting them with waves of numbers first. You can use interactive activities such as polls , word clouds , online quiz and Q&A sections , combined with icebreaker games , to assess their understanding of the data and address any confusion beforehand.

#2 – Use the wrong type of chart

Charts such as pie charts must have a total of 100% so if your numbers accumulate to 193% like this example below, you’re definitely doing it wrong.

Before making a chart, ask yourself: what do I want to accomplish with my data? Do you want to see the relationship between the data sets, show the up and down trends of your data, or see how segments of one thing make up a whole?

Remember, clarity always comes first. Some data visualisations may look cool, but if they don’t fit your data, steer clear of them. 

#3 – Make it 3D

3D is a fascinating graphical presentation example. The third dimension is cool, but full of risks.

Can you see what’s behind those red bars? Because we can’t either. You may think that 3D charts add more depth to the design, but they can create false perceptions as our eyes see 3D objects closer and bigger than they appear, not to mention they cannot be seen from multiple angles.

#4 – Use different types of charts to compare contents in the same category

This is like comparing a fish to a monkey. Your audience won’t be able to identify the differences and make an appropriate correlation between the two data sets. 

Next time, stick to one type of data presentation only. Avoid the temptation of trying various data visualisation methods in one go and make your data as accessible as possible.

#5 – Bombard the audience with too much information

The goal of data presentation is to make complex topics much easier to understand, and if you’re bringing too much information to the table, you’re missing the point.

The more information you give, the more time it will take for your audience to process it all. If you want to make your data understandable and give your audience a chance to remember it, keep the information within it to an absolute minimum. You should set your session with open-ended questions , to avoid dead-communication!

What are the Best Methods of Data Presentation?

Finally, which is the best way to present data?

The answer is…

There is none 😄 Each type of presentation has its own strengths and weaknesses and the one you choose greatly depends on what you’re trying to do. 

For example:

• Go for a scatter plot if you’re exploring the relationship between different data values, like seeing whether the sales of ice cream go up because of the temperature or because people are just getting more hungry and greedy each day?
• Go for a line graph if you want to mark a trend over time. 
• Go for a heat map if you like some fancy visualisation of the changes in a geographical location, or to see your visitors’ behaviour on your website.
• Go for a pie chart (especially in 3D) if you want to be shunned by others because it was never a good idea👇

What is chart presentation?

A chart presentation is a way of presenting data or information using visual aids such as charts, graphs, and diagrams. The purpose of a chart presentation is to make complex information more accessible and understandable for the audience.

When can I use charts for presentation?

Charts can be used to compare data, show trends over time, highlight patterns, and simplify complex information.

Why should use charts for presentation?

You should use charts to ensure your contents and visual look clean, as they are the visual representative, provide clarity, simplicity, comparison, contrast and super time-saving!

What are the 4 graphical methods of presenting data?

Histogram, Smoothed frequency graph, Pie diagram or Pie chart, Cumulative or ogive frequency graph, and Frequency Polygon.

Leah Nguyen

Words that convert, stories that stick. I turn complex ideas into engaging narratives - helping audiences learn, remember, and take action.

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More from AhaSlides

Data visualization is the representation of data through use of common graphics, such as charts, plots, infographics and even animations. These visual displays of information communicate complex data relationships and data-driven insights in a way that is easy to understand.

Data visualization can be utilized for a variety of purposes, and it’s important to note that is not only reserved for use by data teams. Management also leverages it to convey organizational structure and hierarchy while data analysts and data scientists use it to discover and explain patterns and trends.  Harvard Business Review  (link resides outside ibm.com) categorizes data visualization into four key purposes: idea generation, idea illustration, visual discovery, and everyday dataviz. We’ll delve deeper into these below:

Idea generation

Data visualization is commonly used to spur idea generation across teams. They are frequently leveraged during brainstorming or  Design Thinking  sessions at the start of a project by supporting the collection of different perspectives and highlighting the common concerns of the collective. While these visualizations are usually unpolished and unrefined, they help set the foundation within the project to ensure that the team is aligned on the problem that they’re looking to address for key stakeholders.

Idea illustration

Data visualization for idea illustration assists in conveying an idea, such as a tactic or process. It is commonly used in learning settings, such as tutorials, certification courses, centers of excellence, but it can also be used to represent organization structures or processes, facilitating communication between the right individuals for specific tasks. Project managers frequently use Gantt charts and waterfall charts to illustrate  workflows .  Data modeling  also uses abstraction to represent and better understand data flow within an enterprise’s information system, making it easier for developers, business analysts, data architects, and others to understand the relationships in a database or data warehouse.

Visual discovery

Visual discovery and every day data viz are more closely aligned with data teams. While visual discovery helps data analysts, data scientists, and other data professionals identify patterns and trends within a dataset, every day data viz supports the subsequent storytelling after a new insight has been found.

Data visualization

Data visualization is a critical step in the data science process, helping teams and individuals convey data more effectively to colleagues and decision makers. Teams that manage reporting systems typically leverage defined template views to monitor performance. However, data visualization isn’t limited to performance dashboards. For example, while  text mining  an analyst may use a word cloud to to capture key concepts, trends, and hidden relationships within this unstructured data. Alternatively, they may utilize a graph structure to illustrate relationships between entities in a knowledge graph. There are a number of ways to represent different types of data, and it’s important to remember that it is a skillset that should extend beyond your core analytics team.

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The earliest form of data visualization can be traced back the Egyptians in the pre-17th century, largely used to assist in navigation. As time progressed, people leveraged data visualizations for broader applications, such as in economic, social, health disciplines. Perhaps most notably, Edward Tufte published  The Visual Display of Quantitative Information  (link resides outside ibm.com), which illustrated that individuals could utilize data visualization to present data in a more effective manner. His book continues to stand the test of time, especially as companies turn to dashboards to report their performance metrics in real-time. Dashboards are effective data visualization tools for tracking and visualizing data from multiple data sources, providing visibility into the effects of specific behaviors by a team or an adjacent one on performance. Dashboards include common visualization techniques, such as:

• Tables: This consists of rows and columns used to compare variables. Tables can show a great deal of information in a structured way, but they can also overwhelm users that are simply looking for high-level trends.
• Pie charts and stacked bar charts:  These graphs are divided into sections that represent parts of a whole. They provide a simple way to organize data and compare the size of each component to one other.
• Line charts and area charts:  These visuals show change in one or more quantities by plotting a series of data points over time and are frequently used within predictive analytics. Line graphs utilize lines to demonstrate these changes while area charts connect data points with line segments, stacking variables on top of one another and using color to distinguish between variables.
• Histograms: This graph plots a distribution of numbers using a bar chart (with no spaces between the bars), representing the quantity of data that falls within a particular range. This visual makes it easy for an end user to identify outliers within a given dataset.
• Scatter plots: These visuals are beneficial in reveling the relationship between two variables, and they are commonly used within regression data analysis. However, these can sometimes be confused with bubble charts, which are used to visualize three variables via the x-axis, the y-axis, and the size of the bubble.
• Heat maps:  These graphical representation displays are helpful in visualizing behavioral data by location. This can be a location on a map, or even a webpage.
• Tree maps, which display hierarchical data as a set of nested shapes, typically rectangles. Treemaps are great for comparing the proportions between categories via their area size.

Access to data visualization tools has never been easier. Open source libraries, such as D3.js, provide a way for analysts to present data in an interactive way, allowing them to engage a broader audience with new data. Some of the most popular open source visualization libraries include:

• D3.js: It is a front-end JavaScript library for producing dynamic, interactive data visualizations in web browsers.  D3.js  (link resides outside ibm.com) uses HTML, CSS, and SVG to create visual representations of data that can be viewed on any browser. It also provides features for interactions and animations.
• ECharts:  A powerful charting and visualization library that offers an easy way to add intuitive, interactive, and highly customizable charts to products, research papers, presentations, etc.  Echarts  (link resides outside ibm.com) is based in JavaScript and ZRender, a lightweight canvas library.
• Vega:   Vega  (link resides outside ibm.com) defines itself as “visualization grammar,” providing support to customize visualizations across large datasets which are accessible from the web.
• deck.gl: It is part of Uber's open source visualization framework suite.  deck.gl  (link resides outside ibm.com) is a framework, which is used for  exploratory data analysis  on big data. It helps build high-performance GPU-powered visualization on the web.

With so many data visualization tools readily available, there has also been a rise in ineffective information visualization. Visual communication should be simple and deliberate to ensure that your data visualization helps your target audience arrive at your intended insight or conclusion. The following best practices can help ensure your data visualization is useful and clear:

Set the context: It’s important to provide general background information to ground the audience around why this particular data point is important. For example, if e-mail open rates were underperforming, we may want to illustrate how a company’s open rate compares to the overall industry, demonstrating that the company has a problem within this marketing channel. To drive an action, the audience needs to understand how current performance compares to something tangible, like a goal, benchmark, or other key performance indicators (KPIs).

Know your audience(s): Think about who your visualization is designed for and then make sure your data visualization fits their needs. What is that person trying to accomplish? What kind of questions do they care about? Does your visualization address their concerns? You’ll want the data that you provide to motivate people to act within their scope of their role. If you’re unsure if the visualization is clear, present it to one or two people within your target audience to get feedback, allowing you to make additional edits prior to a large presentation.

Choose an effective visual:  Specific visuals are designed for specific types of datasets. For instance, scatter plots display the relationship between two variables well, while line graphs display time series data well. Ensure that the visual actually assists the audience in understanding your main takeaway. Misalignment of charts and data can result in the opposite, confusing your audience further versus providing clarity.

Keep it simple:  Data visualization tools can make it easy to add all sorts of information to your visual. However, just because you can, it doesn’t mean that you should! In data visualization, you want to be very deliberate about the additional information that you add to focus user attention. For example, do you need data labels on every bar in your bar chart? Perhaps you only need one or two to help illustrate your point. Do you need a variety of colors to communicate your idea? Are you using colors that are accessible to a wide range of audiences (e.g. accounting for color blind audiences)? Design your data visualization for maximum impact by eliminating information that may distract your target audience.

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What It Takes to Give a Great Presentation

• Carmine Gallo

Five tips to set yourself apart.

Never underestimate the power of great communication. It can help you land the job of your dreams, attract investors to back your idea, or elevate your stature within your organization. But while there are plenty of good speakers in the world, you can set yourself apart out by being the person who can deliver something great over and over. Here are a few tips for business professionals who want to move from being good speakers to great ones: be concise (the fewer words, the better); never use bullet points (photos and images paired together are more memorable); don’t underestimate the power of your voice (raise and lower it for emphasis); give your audience something extra (unexpected moments will grab their attention); rehearse (the best speakers are the best because they practice — a lot).

I was sitting across the table from a Silicon Valley CEO who had pioneered a technology that touches many of our lives — the flash memory that stores data on smartphones, digital cameras, and computers. He was a frequent guest on CNBC and had been delivering business presentations for at least 20 years before we met. And yet, the CEO wanted to sharpen his public speaking skills.

• Carmine Gallo is a Harvard University instructor, keynote speaker, and author of 10 books translated into 40 languages. Gallo is the author of The Bezos Blueprint: Communication Secrets of the World’s Greatest Salesman  (St. Martin’s Press).

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Presentation Of Data: Finding The Purpose & Why In Data

Chetan saiya.

The presentation of data is not as easy as people think.  There is an art to taking data and creating a story out of it that fulfills the purpose of the presentation.  We’ve seen 100’s of presentations and we’ve developed our own best practices when presenting data to any audience.  Some of these insights are fairly straightforward while others are less obvious.  But overall, these tips should allow you to better organize, visualize, and verbalize your presentations with success and ease.

Reduce Text & Create More Visuals

Many case when we’re presenting big data sets, we think that having plenty of text on the graphs can be a good thing because it helps explain the graph a little better.  This is in fact a bad idea because it makes the graph look more jumbled and does not present well as people try to take in the visual nature of the data set that is being presented. More texts in graphs don’t look good. For your presentation, you need clear graphics with fewer texts and, for that, an experienced writer or help to write presentation texts.  Here is an example of a presentation with plenty of data but too much text.

This is something that must be well thought out.  Line graphs, bar graphs, and pie graphs do matter depending on the context and the message you’re looking to portray to your audience.  Line graphs are great for time based data presentations.  Bars are great for groupings.  Pies are perfect for percentages of things.  Knowing which type of graph makes the most sense can help in presenting the data to your audience.

Consolidate Data

There are times when we present data and we don’t take advantage of consolidating multiple graphs into one graph.  A great example is looking at the growth in search engine marketing across multiple device platforms including desktop, tablet, and mobile.  One could create 3 separate graphs showcasing the growth in search engine marketing via 3 separate bar graphs, but combing them into 1 graph creates a more powerful image for the audience.  In the graph below, this could have been broken out into three separate graphs, but the presenter decided to consolidate into one graph.

Create Simplicity In Your Data

Try not to make the data look too complicated.  In the previous section we discussed consolidating data but there are cases when too much consolidation can be too complex for the eyes of the audience to consume.  Remember that your audience has the arduous task of going back and forth between you and the graphs you’re speaking to.  Constructing the graphs as simple as you can make them will make it easier for your audience to grasp your message.

Place labels close to data points

Data legends and labels are often absent. The presenter assumes that the audience will follow their verbal cues. Or, when legends and labels are present, they are often presented far away from associated data points. This forces the audience to visually scan back and forth.  When you are creating a legend, place the points close together in the corner upper right or bottom right of the graph.  This way, the audience can easy view the points and scan back to the graph as you’re speaking to it.

Leverage Video For Data Presentations

Video is our friend.  It engages people, mixes up the visuals, and helps portray a message and tell a story.  After a particular data set, don’t be afraid to throw in a video that helps augment the purpose or reasoning behind the data.

Explain the data axes

You may think this is simple and people will automatically get it but explaining the axis before any presentation is nonetheless important.  All it should take you is 5 – 15 seconds to give a basic understanding of what the axes mean.

Don’t Be Afraid To Dig A little deep into numbers

Without being complicated, don’t be shy in explaining the numbers.  Talking numbers is never fun for an audience but if there are ways to incorporate the graph and data into a story that serves purpose and meaning to the presentation, work to do it.  You can never assume the audience fully understands what you are saying or conveying so digging deep into the numbers can be critical to getting your message home.

Find Brand Consistency In Your Data

Don’t be afraid to use more brand consistency and color schemes in your data sets.  It’s nice to portray your brand and doing so with similar colors and text helps augment your brand from the beginning to end of the presentation.

Answer the “Why?” questions

When you’re presenting data, the audience always wants to know why.  Why is this important, why does this matter, and why should I care.  Answering the why in your data helps you understand your purpose and the true meaning behind the numbers.

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Visualization Techniques in Healthcare Applications: A Narrative Review

Nehad a abudiyab.

1 Health Informatics, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, SAU

2 Researcher, King Abdullah International Medical Research Center, Riyadh, SAU

Abdullah T Alanazi

3 Researcher, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, SAU

4 Health Sciences, King Abdullah International Medical Research Center, Riyadh, SAU

Nowadays, healthcare management systems are adopting various techniques that facilitate the achievement of the goals of evidence-based medical practice. This review explores different visualization techniques and their importance in healthcare contexts. We performed a thorough search on databases such as the SLD portal, PubMed, and Google Scholar to obtain relevant studies. We selected recent articles published between 2018 and 2021 on visualization techniques in healthcare. The field of healthcare generates massive volumes of data that require visualization techniques to make them easily comprehensible and to guide their efficient presentation. Visualization in healthcare involves the effective presentation of information through graphics, images, and videos. Big data systems handle a massive amount of information and require visualization techniques to present it in a comprehensible manner. The significance of visualization techniques in healthcare is not confined to healthcare practitioners and healthcare management but encompasses all the stakeholders; patients can benefit from the visualization of his/her data for a better understanding of their condition. In short, visualization techniques have demonstrated their benefits in the healthcare sector and can be extended to the payer and the patient. They have also had a positive impact on the quality of the healthcare provided as well as patient safety.

Introduction and background

Data visualization in healthcare sectors relies on sophisticated modern technology that enables professionals from various fields to demonstrate their work and present information efficiently. Visualization techniques assist healthcare providers in understanding the trends that have occurred in the past as well as those in the present and in predicting and anticipating future trends and directions. Generally, data visualization involves representing data and information in various forms, such as graphs, charts, diagrams, and pictures [ 1 ]. These visualization techniques can provide healthcare providers with an easy way to identify and understand data trends, outliers, and patterns [ 2 ]. Visualization techniques have been essential in various healthcare sectors, especially in terms of supporting providers in making important clinical decisions regarding patient and community health. Through various visualization techniques, the healthcare organization can synthesize raw data into graphs and then present it in charts to enable the prompt interpretation of the trends and patterns [ 3 ].

This review aims to explore the different visualization techniques in healthcare, identify the benefits they bring to the field, and provide future directions for visualization-related studies.

This literature review provides a descriptive analysis of the application of visualization techniques in healthcare settings. The review criteria focus on incorporating the available studies in the review context and identifying recent research on visualization techniques in healthcare. The selected articles were obtained from various databases (SLD portal, PubMed, and Google Scholar).

The information about applications of visualization techniques in healthcare sectors is derived from data analysis and presentation. The most viable techniques are employed in the contemporary aspects of data visualization. Statistical analysis is complex to present via data visualization. Hence, it is accomplished through the use of interactive visualization. According to Gartner (2021), interactive visualization can be defined as manipulating graphical information via brightness, color, motion, and shape to elevate the meaning of the presented data [ 4 ]. Distinctly, the core objective of interactive and data visualization is to present and display the information in a way that the stakeholders will be able to interpret the data and increase their knowledge, thereby directly improving the service quality. In this context, many researchers have explored visualization techniques in healthcare sectors.

Historical Context of Data Visualization in Healthcare

One study discussed the application of data visualization in healthcare sectors in the context of what the author calls the Florence effect [ 5 ]. According to this study, the healthcare sector requires using the information in a potent way that propagates efficiency, promoting evidence-based practice [ 5 ]. The implication is that incorporating visualization techniques in healthcare sectors has enabled them to achieve various goals of evidence-based practice. Furthermore, the healthcare sector has established a platform that utilizes data visualization to interpret and assimilate complex healthcare data [ 5 ]. The researcher established the historical context of data visualization by referring to the efforts of Florence Nightingale in the 19th century [ 5 ]. Florence Nightingale was a military nurse who took care of injured British soldiers. Based on her daily treatment of injured soldiers, she accumulated sufficient patient information that could be used to help reduce the mortality of the other wounded soldiers. However, due to patient confidentiality and the strict rules regarding the disclosure of patient information, she designed a statistical representation through pie charts to present data that could help reduce mortality among military personnel. Later, it was discovered that statistical presentation made accessing and interpreting patient information and outcomes easier [ 5 ]. This study is crucial as it provides the historical context regarding the integration of data visualization in healthcare sectors and its importance in monitoring and evaluating healthcare indices.

Types of Data Visualization Techniques

According to the study by Narayan et al. in 2021, accumulating a large volume of healthcare data makes the big data concept very common in the healthcare sectors, considering the aspects of volume, velocity, variety, and veracity of the data [ 6 ]. Visualization techniques make big data less complex and easy to interpret, even for non-healthcare providers. The healthcare sectors need to have tools to develop visualization. Many tools use data visualization techniques, such as pivot tables and charts. Furthermore, different visualization tools are available for those with technical and non-technical backgrounds. For example, Microsoft Excel provides a great visualization tool for healthcare providers with little or no knowledge of technical aspects.

Another example is statistical software such as IBM SPSS and JASP. Statistical software provides interactive visualization systems that can be used by expert providers. These visualization tools can be used in public disease surveillance [ 6 ]. For efficient and prompt healthcare data visualization, it is essential to consider publicizing the information to the stakeholders via various platforms. In public community healthcare, sharing data and integrating visual information into one universal platform is beneficial and necessary. Several types of platforms are available for this purpose, including cloud-based platforms. Moreover, cloud-based platforms such as ParaView and Gephi enable the provider to generate and host the graphics. Furthermore, these platforms could facilitate scientific reproducibility by matching the scientific figures to their underlying data and promoting discussion among collaborators [ 6 ].

Process of Healthcare Data Visualization

Most of the time, data analysis in healthcare sectors incorporates control checks to maintain visualized data accuracy. Electronic health systems are rich in raw data that can be subject to analysis. Analytics data are fed into a learning machine, artificial intelligence tools, and other analysis tools [ 7 ]. These tools provide a visual presentation of healthcare data regarding different aspects, including disease prevalence, patient age that is associated with the most prevalence, and other factors related to the disease. After the analysis, the visual data can be contrasted with other data collected before, and the same analysis and visualization techniques can be applied to them. Also, this effort to contrast the data enables healthcare providers to easily identify the trends and the changes in different aspects that have occurred over a certain period [ 8 ].

Implementation of Data Visualization in Healthcare

The main objective of data visualization in healthcare sectors is to simplify complex data to make them user-friendly so that healthcare providers can easily interpret them.

Interactive Dashboard

According to Pestana et al., dashboards and data analysis tools are usually built into the healthcare systems' existing software [ 9 ]. Usually, the dashboards help with combining several interactive reports. The dashboard is usually classified into three main types: the active type, which usually shows real-time data in healthcare organizations; the strategic type, which displays trends over time; and the analytical type, which presents advanced analytics. An example of data visualization through a dashboard in the Ministry of Health in Saudi Arabia is illustrated in Figure ​ Figure1. 1 . The image shows the dashboard used for analyzing COVID-19 prevalence in Saudi Arabia

COVID-19: coronavirus disease 2019

Advantages of Visualization Techniques in Healthcare Implementing and adopting different visualization techniques in healthcare sectors is vital in enhancing the overall healthcare provision by healthcare providers. Several healthcare facilities have implemented various data analysis tools in healthcare sectors, including machine learning and artificial intelligence. There are several benefits to implementing and adopting such techniques in healthcare facilities, and some of these are as follows: I. Improving overall patient care: utilizing health data visualization has positively affected the general provisioning of healthcare. Health data visualization has a significant role in supporting healthcare providers in their clinical decision-making and facilitating their ability to predict the threat and react immediately. Moreover, these threats were discovered by identifying various measures that permit the situation to be analyzed critically within a healthcare organization. Visualizing patient health data in real-time is crucial for improving the quality of care. It enables the healthcare provider to make the necessary clinical decisions based on the patient's situation [ 10 ]. For example, data visualization techniques help in monitoring various healthcare parameters, such as oxygen saturation [ 11 ]. Furthermore, patients' oxygen saturation levels and treatment can be analyzed in real-time to evaluate their responses to the treatment provided. For instance, during the coronavirus disease 2019 (COVID-19) pandemic, many patients developed lung disease due to severe pneumonia infection. Moreover, those patients were suffering from breathing difficulties and a decrease in their oxygen saturation level. Using data visualization techniques that involved displaying data on the monitoring machines was vital in assessing patients' responses to the oxygen level provided through the ventilator machine [ 12 ]. In various inpatient units, real-time data visualization has been used to monitor other patient parameters such as pulse, heart rate, and blood pressure [ 13 ]. Again, these real-time data visualizations significantly helped the providers to detect abnormal parameters and facilitate the intervention needed to improve patient outcomes and overall healthcare quality in the healthcare facility. II. Disease trend and pattern recognition: identifying trends and patterns is another significant advantage of utilizing visualization techniques in healthcare sectors. Determining the trends in healthcare is vital for making decisions regarding healthcare provision. Moreover, one of the critical trends in healthcare sectors is identifying and assessing disease patterns among specific populations. The trend of the disease patterns is an important attribute that should be monitored closely as it provides the necessary indications to investigate the factors causing an elevation in the trend. Data analysis and visual presentation on obesity is a good example of trend and pattern recognition; it acts as an indicator for public and community health. Identifying the factors behind the trends can help raise awareness about modifying the lifestyles of the patients as well as the general public [ 14 ]. III. Data presentation for various audiences: most of the time, healthcare data are more challenging to interpret among providers working in different disciplines compared to individuals with no medical background. Moreover, the primary purpose of data presentation is to simplify complex data so that it can be easily interpreted by any audience regardless of their background. An example of simplifying the data for disease prevalence is displaying it in graphics to the audience [ 1 ]. Also, utilizing the presentation to illustrate some of the factors affecting disease prevalence makes the medical data valuable and easily accessible to any intended audience. IV. Accelerated performance: Another advantage of real-time data visualization in a healthcare organization is accelerating the performance of the healthcare provided through several measures, such as ensuring prompt clinical decision-making in critical situations, which will positively impact patient prognosis and health status. Furthermore, accelerated performance can reduce the inadequacies of the provided care. Hence, accelerated performance can guarantee the overall better performance of healthcare organizations by building a good reputation for efficiency and better patient outcomes [ 2 ]. V. Errors and fraud detection: the most prominent benefit of implementing various data analytics and visualization techniques in healthcare sectors is that it enables the detection of frauds and errors that occur within healthcare organizations, such as errors and frauds in medical billing. According to the report published by Medicare and Medicaid, most of the fraud cases that occur within healthcare facilities are committed by the healthcare providers who work in the healthcare facility. Moreover, fraud cases usually cost healthcare facilities losses amounting to 58.5 to 89.3 billion dollars [ 14 ]. The most prevalent forms of billing fraud in healthcare facilities are duplicate billing, phantom billing, false prescription, and other types of insurance fraud by healthcare providers. Furthermore, clear and proper correlation among the stakeholders, including patients, healthcare payers, and providers regarding claims can enhance the integrity of the billing process and decrease fraudulent schemes [ 15 ]. Implementing data visualization techniques has significantly improved transparency in the healthcare sector.

Benefits of the review

Several advantages can be drawn from this literature review. It can be a source of information for researchers and students seeking knowledge on the same or similarly relevant topics. Moreover, the literature content has been designed in such a way that the audience can easily grasp and comprehend the information. In addition, the review can serve as a platform for identifying the loopholes in the application of visualization techniques in healthcare sectors based on recently published scientific research [ 16 ]. Also, it is essential to highlight that the review discussed several strategies that could help the medical professional improve the care delivered to the patient based on the best practices and applications of visualization techniques. It should be noted that some of the studies selected for this literature review are not directly about visualization techniques in the healthcare sector. We have made an effort to expand the scope of the review and explore the broader implications of the impact of visualization techniques.

Future directions

This review was based on recently published articles. It has certain drawbacks and loopholes that can be addressed by future research to enhance patient outcomes and quality management in healthcare sectors. There are some areas that need further investigation, including the use of interactive visualization techniques and their impact on healthcare sectors. In addition, only some of the studies included dealt with interactive visualization techniques, and studies have yet to analyze the importance of these techniques to healthcare facilities. Another area that needs further investigation is the role of patient-oriented visualization tools and their ability to support patients' health and outcomes [ 17 ]. Further studies need to be conducted by focusing on these topics, which would enhance and improve the knowledge base in terms of utilizing visualization techniques in healthcare sectors.

Limitations of the review

This review fully relied on published articles of the research that other scholars have conducted. Hence, our findings are wholly based on secondary knowledge obtained from peer-reviewed sources. These resources might include some errors that might impact the findings of this review as well.

Conclusions

This review article highlighted the importance of data visualization techniques in healthcare from the standpoint of the following main benefits: improving the healthcare provided, prompt diagnosis of the disease, recognizing the patterns, simplifying the presentation of the healthcare data, accelerating healthcare performance, and improving error detection. The concept of visualization has been one of the significant innovations implemented and adopted in various healthcare facilities. Data visualization has several advantages and hence most healthcare facilities have embraced and implemented it in their day-to-day functioning. Moreover, the benefits of visualization techniques are clearly reflected in their effectiveness in the decision-making process, resulting in improved patient safety and quality of care. In addition, identifying the pattern and disease recognition via the presented data can provide vital knowledge in terms of treatment, diagnosis, and even adopting new policies in healthcare facilities. Also, it enhances the transparency of medical billing by reducing errors and fraud cases in healthcare facilities. Therefore, visualization techniques in healthcare sectors encompass many stakeholders, such as patients, healthcare practitioners, payers, and healthcare management. Also, we discussed the main limitations and challenges faced while conducting this literature review. Lastly, this review provides insight into the potential directions that future efforts on this topic can adopt.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

What Is a Digital Presentation & How to Get Good At It

Learn the basics of presentation decks and how to create one. Explore examples and tips to make your own deck more effective and engaging.

Dominika Krukowska

16 minute read

Short answer

What is a presentation.

A presentation is a slide-based visual storytelling aid. It’s used for transferring information and emotion to an audience with visual, vocal, and textual communication.

The purpose of a presentation is to help the audience understand a subject matter. Presentations are used in business, academics, and entertainment. They can be made in PowerPoint, PDF, or webpage format.

Why people hate presentations (including yours)

Have you ever sat through a digital presentation that felt like it was dragging on forever? Or worse, have you been the one giving the presentation when people’s eyes glazed over?

This feeling of agonizing boredom is called Death by PowerPoint, and it means losing your audience's attention. They won't remember anything you said, and probably couldn't care less.

I’m going to show you how to never again suffer from Death by PowerPoint by avoiding the common PowerPoint pitfalls, immediately engage your audience, capture their interest, and make them care.

Let's dive in!

What is the main purpose of a presentation?

The purpose of a presentation is to communicate information or ideas to an audience in a clear and effective manner. The reasons for making a presentation can be to inform, persuade, motivate, educate, entertain, or simply share knowledge or experiences.

The goal of a presentation can be to help your audience understand complex concepts, make informed decisions, or take action based on the information you present.

In business settings, presentations are often used to pitch products or services, report on progress or performance, or make recommendations to stakeholders.

What are the 2 main types of presentations?

When it comes to creating a presentation, there are 2 primary types: (1) speech presentations and (2) digital presentations (made for reading). There are key takeaways for nailing each presentation type. Take note of them if you intend to get good at both.

Reading presentations

Speech presentations

Digital presentations (Reading presentations)

Digital presentations, on the other hand, are presentations that the audience can access on their own computer or phone without the presenter being physically present. These presentations require a different set of skills and techniques to keep the audience engaged.

Essentials for improving your digital presentations:

• Written clarity is critical: Since your audience will be reading your presentation, it's essential to keep your content clear and concise. Say more with less.
• Show, don't tell: Use supporting visuals to help illustrate your points and make your presentation more engaging.
• Animation and annotation: Use animations and annotations to direct your audience's attention to the right place at the right time, keeping them engaged throughout. there are plenty of free animation software to help you create these.
• Personalization: Make your audience feel like you're speaking directly to them by personalizing your presentation. Use inclusive language and address their pain points, needs, and interests.

Speech presentations (Face to face)

Speech presentations are the classic type of presentation where a speaker presents to an audience in person. These presentations are usually given at conferences or meetings, and can now also take place virtually through platforms like Zoom, Google Meet, or Skype.

Essentials for improving your speech presentations:

• Less written, more spoken: Speech presentations are all about the spoken word, so it's crucial to avoid cramming too much text onto your slides. Focus on speaking to your audience instead.
• Body language and voice: In a speech presentation, your body language and tone of voice are essential to engaging your audience. Use humor, sarcasm, or suspense to keep your listeners interested.
• Rapport: Making eye contact and using real-time communication can help you build rapport with your audience and make them feel involved in your presentation.

What are the main types of digital presentations?

Digital presentations come in all shapes and sizes, but understanding the main types can help you choose the right format for your message.

Business presentations

Marketing presentations, sales presentations, education and training presentations, personal presentations.

Education & training

Business presentations are used for showcasing company performance updates, introducing new products or services, discussing future plans with clients and partners, or briefing investors.

Whether it's an internal meeting or an external one with stakeholders, business presentations are all about delivering a clear and compelling message that drives the company forward.

Marketing presentations are visual decks used to present your target audience, marketing strategies, and campaign outcomes to prospective clients, ad agencies, or stakeholders.

Sales presentations are decks that contain details about the features, pricing, and main benefits of your offering, and are used during in-person meetings or online sales calls. They’re designed to help sales reps close deals or land new clients.

Education and training presentations are slide decks designed to teach new concepts and best practices to a variety of audiences, including students, employees, or clients.

A personal presentation is used during networking events, business conferences, or public speaking engagements. It’s used to share your key accomplishments and demonstrate your passion and the main values you stand for.

What makes a good presentation?

A good presentation captivates by establishing trust, engaging the audience with interactive elements, and weaving data into an enthralling narrative that sparks emotions and inspires, leaving a lasting impact.

There are 3 things any good presentation must do:

1. Establish trust and credibility

Without your audience trusting you and your authority you will never get them to listen. And to really listen, some say, they have to like you.

To establish yourself as a credible source of information, use relevant visuals, stories, and examples that showcase your expertise and experience, earning the trust of your audience.

2. Interact with the audience

Static PowerPoint slides are no longer enough to engage anyone. Presentations need to be informative but also entertaining.

Therefore, incorporating interactive elements into your presentations like animations, videos, calculators, quizzes , polls, and live infographics is now essential to grab attention and keep your audience engaged start-to-finish .

3. Tell a good story

When it comes to digital presentations, it's not just about the information you share, but how you share it. That's where storytelling comes in! It's all about weaving a relatable narrative that resonates with your viewers, leaving them eager for more.

By blending your data and facts into an enthralling tale, you're not only dishing out knowledge but also sparking emotions and inspiration. It's a game-changer for grabbing your audience's attention and getting your message across effectively.example

How to create a good digital presentation?

To create a great digital presentation, you need to think beyond the slides and consider the experience you want your audience to have.

Think of your presentation as a journey that takes your audience from point A to point B - you need to ensure that every step of the way is memorable and captivating.

When creating a digital presentation, there's more to it than just putting together a few slides.

You can make it real-pretty, but to make it truly effective you need to have a clear understanding of where you want to take your audience, and tailor your content accordingly.

Good presentation example

This example shows how interactive content can make a presentation that pulls you in and makes you feel part of the journey.

What should a presentation include?

Most decks contain the following 3 elements:

• Introduction (the objectives and agenda of your presentation)
• Main body (key talking points that you want to cover)
• Conclusion (followed by a single, actionable call to action)

The specific outline of your presentation will depend on your particular use case.

Check out our dedicated guides for particular business presentations:

• What to Include in a Pitch Deck (Slides 99% of Investors Want)
• 7 elements of a great sales deck structure
• What should a one-pager include?
• What does a marketing deck include?

How to start and how to end a presentation?

Start your presentation with a strong hook that captures your audience's attention and makes them interested in what you have to say.

You can end your presentation with a thank you slide, but that would be too bad. For your words to carry beyond the last slide you’ll need to give your audience the next step.

And so, you should end your presentation with a singular, clear call to action that inspires your audience to follow through on your message.

What are the essential building blocks of a successful presentation?

Almost everyone nowadays makes beautiful presentations. But that’s not enough to make them successful.

5 key elements that every successful presentation includes:

1. Compelling (human) story: Your presentation should tell a story that connects with your audience on a personal and emotional level, making your message relatable and memorable.

Here are 5 quick storytelling tips to deliver engaging presentations:

2. Clear structure: A clear structure helps your audience follow along and understand the flow of your presentation. This can be chronological, sequential, before-after, problem-solution-resolution, or any other simple and easy-to-follow structure.

3. Problem and solution: Your presentation should address a problem that your audience faces and offer a solution that your product or service can provide.

4. Actionable takeaways: Your presentation should leave your audience with actionable steps or insights that they can use to apply the information you've presented.

5. Supporting visuals (product demo) and data visualization (graphs, charts, and infographics): Using visuals to support your presentation can reinforce your message and help your audience retain the information you presented.

6 biggest mistakes to avoid when creating a presentation

It’s easy to forget that the presentation is for your audience rather than for you. You may want to tell them everything from A to Z, but they may only want to know ABC.

It’s even easier to take for granted that the things you understand are clear to others. But for them, these things are horribly complex (look up the curse of knowledge).

1. Using too much text: Overloading your slides with text can cause your audience to lose interest and detract from your main points. Keep your text to a minimum and use visuals to reinforce your key takeaways.

2. Going too much into detail: attention is a limited resource so you can’t fit everything in a single presentation. Tell your audience only what they really want (and need) to know. Avoid any technical details or complex jargon that does not contribute to the core of your message.

3. Neglecting interactivity: Failing to include interactive elements can cause your audience to disengage. Use polls, quizzes, and other interactive tools, including email newsletter software , to keep your audience engaged.

4. Ignoring the power of storytelling: Telling a compelling story is critical to capturing your audience's attention and leaving a lasting impression. Use relatable stories and examples that support your key points.

5. Poor use of visuals: Using low-quality visuals, irrelevant images, or poorly designed charts and graphs can detract from your presentation and cause confusion. Use high-quality visuals that reinforce your key ideas and are easy to understand.

6. Lack of personalization: If you don’t tailor your presentation to your audience's needs, interests, and level of understanding, your message will fall flat. Make sure to consider your audience's perspective and adjust your deck accordingly.

You don't want your presentation to end up looking like this:

How to design a presentation?

Designing a presentation is a bit like decorating a cake - you want it to be visually appealing but also yummy to consume. You want it to leave your audience with a taste for more rather than a bad taste in their mouth.

Lucky for you there are practical steps for designing a presentation that truly wows your audience every time. There's also a more practical presentation maker for this than PowerPoint. You can use it to get much more engaging presntations.

Practical presentation design tips:

1. Choose a color scheme: Just like choosing the perfect icing color for your cake, selecting a color scheme that complements your brand can make your presentation feel more coherent. Or, if you’re pitching to a client, you can use their brand colors instead in order to impress them.

2. Use high-quality images: Using high-quality images is like adding a layer of delicious, rich frosting to your cake. It makes your presentation more visually interesting and helps support your key message.

3. Use consistent fonts: Using consistent fonts throughout your presentation can make it easier to read. Stick to two or three fonts that complement each other and use them consistently.

4. Incorporate visual aids: Visual aids like colorful sprinkles and creative cake toppers can take your cake to the next level. Similarly, graphs, charts, and infographics can help break text patterns and, therefore, make your presentation more memorable.

Check out our use-ready slide design with every type of slide you can think of designed according to our tips and best practices.

Where to find presentation templates?

Scouring the web for presentation templates can be a bit like looking for a needle in a haystack - it's time-consuming, frustrating, and can leave you feeling a bit lost. Most designs available look dull and samey, and are not optimized for engagement.

But don't worry, we've got you covered! Here are the best interactive presentation templates for different use cases:

Choose template by:

What tools to use to create presentations?

Unfortunately, there's no one-size-fits-all tool for creating a digital presentation. And with so many presentation tools out there, it can be hard to know where to start looking.

That’s why we've done the research for you - check out our article rounding up the best presentation software to pick the right one for your needs!

And, if you want to learn more about creating effective digital presentations, check out these posts:

• How to Make Effective & Impactful Presentations (12 Steps)
• How to Make a Multimedia Presentation (5 Easy Steps)

How to give a presentation?

Giving a presentation can be intimidating, but it's an excellent opportunity to showcase your knowledge and expertise. To deliver a successful presentation, you need to focus on engaging your audience, keeping their attention, and providing valuable information.

9 tips to help you give a memorable presentation:

1. Start with a strong hook

A strong opening is crucial to grab your audience's attention and pique their interest. Begin with a bold statement, a surprising fact, or a personal anecdote that relates to the topic of your presentation. This will immediately grab the audience's attention and make them want to listen to what you have to say.

2. Make your objectives and agenda clear

Engage your audience right from the start by letting them know what's in store for them. Outlining your objectives and agenda early on will keep your audience focused and ensure that they don't miss out on any crucial information. Let them know why it's important to pay attention to your presentation and what they can expect to learn from it. By doing this, you'll build anticipation and get them excited about what's to come!

3. Leverage storytelling

People love stories, and they are an effective way to connect with your audience. Use anecdotes, metaphors, and examples to illustrate your points and make your presentation more relatable. This will help the audience understand the concepts you're presenting and retain the information up to 60-70% better .

4. Ask questions, use humor, give simple directions that prove a point

Engage your audience by asking questions, using humor, and giving them simple tasks to perform that illustrate your point. This will keep their attention and make the presentation more interactive.

5. Direct the audience's attention

Use a pointer or built-in animation to draw the audience's attention to critical information. This will help them focus on what you're saying and avoid distractions.

6. Work on the delivery

Speak slowly and clearly, use positive language, and avoid reading from notes as much as possible. Use humor and engage with your audience to make the presentation more enjoyable. Ensure your body language is confident and relaxed, and maintain eye contact with your audience.

7. Add interactive elements

Incorporate interactive elements like polls, quizzes, or surveys to involve your audience and gather valuable feedback. This will make your presentation more engaging and ensure your audience retains the information presented.

8. Close with a CTA

End your presentation with a strong call to action (CTA). Inspire your audience to take the next step, whether it's signing up for a newsletter, buying a product, or visiting your website. Make it clear what you want your audience to do after the presentation.

9. Leave time for a Q&A session

Finally, leave ample time for a Q&A session. This will allow your audience to clarify any doubts and ask questions. It's also an excellent opportunity for you to engage with your audience and get valuable feedback on your presentation.

Create amazing digital presentations from templates

Creating a digital presentation that grabs your audience's attention and drives results may feel like a daunting task.

After all, a strong digital presentation can be the difference between leaving a lasting impression on your audience or falling flat and losing their attention.

It's like trying to teach a class without proper preparation - you're not giving your knowledge and expertise a chance to shine, and your audience might not retain the information you're presenting.

To make things easier, try using our customizable digital presentation templates that will help you create an engaging and impactful digital presentation in no time!

Where can I see examples of good presentations?

If you’re looking for real-life examples that drove results for other companies from different industry sectors, check out highly effective presentation examples by our clients .

Alternatively, if you want to see the best presentation examples that you can replicate to create your own, here are our dedicated guides:

• 10 Perfect Presentation Examples That Win Over Anyone
• 9 Unique Sales Deck Examples that Outsell the Rest
• 10 Top Pitch Deck Examples to Inspire Your Fundraising Efforts
• Top Product Presentation Examples That Wow Everyone
• Marketing Deck: What It Is & How to Make It Win (Examples)
• 6 Elevator Pitch Examples for Any Scenario (Ready for Use)

Where can I find good presentation templates?

If you’re looking for snazzy presentation templates, Storydoc should be your go-to place. We offer a fantastic selection of visually stunning designs to make your digital presentation pop.

All components have been designed with best practices in mind and optimized for engagement. Thanks to the built-in analytics panel, you can also check how your presentations perform in real-time.

Click on any of these categories to see the best presentation templates for your specific use case:

• One-pager templates
• Sales deck templates
• Pitch deck templates
• Business proposal deck templates
• Marketing decks templates
• Case studies templates
• Report templates
• White paper templates

What are common types of business presentations?

The most common types of business presentations are:

• Sales decks
• Pitch decks
• Business proposal decks
• Marketing decks
• Case studies

Is a presentation the same as a slideshow?

Technically, a slideshow is a type of presentation, but not all presentations are slideshows.

A presentation can take many different forms, from a speech to a product demonstration, and can use various tools, including slideshows, to deliver the message. So while a slideshow is certainly a popular choice for presentations, it's not the only option out there.

What is death by PowerPoint?

Death by PowerPoint is the phenomenon of boring, uninspired, and ineffective presentations that use an overabundance of bullet points, text-heavy slides, and monotonous delivery. It's a surefire way to put your audience to sleep and leave them counting down the minutes until your presentation is over.

To avoid death by PowerPoint, aim to create presentations that are visually engaging, incorporate storytelling, and use multimedia elements like images, videos, and interactive features. Remember, a presentation should be a tool to enhance your message, not a crutch to lean on.

What are common types of presentation delivery formats?

There are 5 popular types of presentation delivery formats to choose from:

• Powerpoint: A classic choice, PowerPoint offers a range of design and animation options to create static slide-based presentations.
• Google Slides : As a cloud-based tool, Google Slides makes it easy to collaborate with others in real-time. It's an excellent option for static team presentations and remote work situations.
• Keynote : Exclusive to Apple devices, Keynote is known for its sleek and elegant design options. It's an ideal choice for visually appealing presentations on Mac or iOS devices.
• PDF: For a simple, static, and easily shareable format, PDF presentations are a reliable option. They ensure consistent formatting across different devices and platforms.
• Storydoc : Taking presentations to the next level, Storydoc provides immersive and interactive templates that are sure to captivate your audience and leave a lasting impression.

What are common types of presentation speech formats?

There are 4 common types of presentation delivery formats:

• Memorized: In a memorized delivery, the presenter memorizes the entire presentation word-for-word and delivers it without notes. This format can be effective for short presentations or speeches but can be challenging to execute for longer presentations.
• Manuscript: In a manuscript delivery, the presenter reads from a written script or teleprompter. This format is great for delivering complex or technical information but can come across as less engaging.
• Impromptu: In an impromptu delivery, the presenter delivers a presentation without prior preparation or planning. This format is often used in situations like interviews or meetings and requires quick thinking and adaptability.
• Extemporaneous: In an extemporaneous delivery, the presenter delivers a presentation using notes or an outline, but not a fully scripted presentation. This format allows for flexibility and engagement with the audience while still maintaining structure.

Why is a presentation important for my business?

Here are the main reasons why presentations are essential for your business:

• Be the expert: Presentations provide a platform to showcase your expertise and share your unique perspectives with your audience, establishing you as a thought leader in your industry.
• Build connections: Presentations provide an opportunity to connect with your audience, building relationships that can lead to future business opportunities.
• Leave a lasting impression: An engaging and memorable presentation can leave a lasting impact on your audience, increasing brand awareness and improving message retention.
• Achieve your goals: Presentations can be used to achieve business goals, from generating leads to securing funding or closing deals.

How to measure the effectiveness of a presentation?

Measuring the effectiveness of a presentation is crucial to ensure it hits the mark with your audience and achieves its goals. Here are some ways to measure the effectiveness of a presentation:

Ask for feedback: Don't be afraid to ask your audience for feedback after the presentation, either through surveys or live feedback. This feedback can provide valuable insights into what worked well and what could be improved, helping you refine your approach for future presentations.

Monitor engagement: Keep a pulse on engagement metrics such as views, shares, or the average reading time if the presentation is delivered online. These metrics can give you a sense of the level of interest generated by the presentation and which parts resonated with your audience. Our own presentation maker comes with built-in analytics tracking and reporting .

Track business outcomes: If your presentation is designed to drive business results, track metrics such as lead generation, sales, or conversion rates to assess its effectiveness in achieving these goals.

Hi, I'm Dominika, Content Specialist at Storydoc. As a creative professional with experience in fashion, I'm here to show you how to amplify your brand message through the power of storytelling and eye-catching visuals.

Perfect Presentation Examples That Win Over Anyone

Top Product Presentation Examples That Wow Everyone Sales and Marketing Presentations Statistics Marketing Presentation Examples that Engage & Convert

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• Accountancy
• Business Studies
• Organisational Behaviour
• Human Resource Management
• Entrepreneurship
• CBSE Class 11 Statistics for Economics Notes

Chapter 1: Concept of Economics and Significance of Statistics in Economics

• Statistics for Economics | Functions, Importance, and Limitations

Chapter 2: Collection of Data

• Methods of Data Collection
• Sources of Data Collection | Primary and Secondary Sources
• Direct Personal Investigation: Meaning, Suitability, Merits, Demerits and Precautions
• Indirect Oral Investigation : Suitability, Merits, Demerits and Precautions
• Difference between Direct Personal Investigation and Indirect Oral Investigation
• Information from Local Source or Correspondents: Meaning, Suitability, Merits, and Demerits
• Questionnaires and Schedules Method of Data Collection
• Difference between Questionnaire and Schedule
• Qualities of a Good Questionnaire and Types of Questionnaires
• What are the Published Sources of Collecting Secondary Data?
• What Precautions should be taken before using Secondary Data?
• Two Important Sources of Secondary Data: Census of India and Reports & Publications of NSSO
• What is National Sample Survey Organisation (NSSO)?
• What is Census Method of Collecting Data?
• Sample Method of Collection of Data
• Methods of Sampling
• Father of Indian Census
• What makes a Sampling Data Reliable?
• Difference between Census Method and Sampling Method of Collecting Data
• What are Statistical Errors?

Chapter 3: Organisation of Data

• Organization of Data
• Objectives and Characteristics of Classification of Data
• Classification of Data in Statistics | Meaning and Basis of Classification of Data
• Concept of Variable and Raw Data
• Types of Statistical Series
• Difference between Frequency Array and Frequency Distribution
• Types of Frequency Distribution

Chapter 4: Presentation of Data: Textual and Tabular

• Textual Presentation of Data: Meaning, Suitability, and Drawbacks

Tabular Presentation of Data: Meaning, Objectives, Features and Merits

• Different Types of Tables
• Classification and Tabulation of Data

Chapter 5: Diagrammatic Presentation of Data

• Diagrammatic Presentation of Data: Meaning , Features, Guidelines, Advantages and Disadvantages
• Types of Diagrams
• Bar Graph | Meaning, Types, and Examples
• Pie Diagrams | Meaning, Example and Steps to Construct
• Histogram | Meaning, Example, Types and Steps to Draw
• Frequency Polygon | Meaning, Steps to Draw and Examples
• Ogive (Cumulative Frequency Curve) and its Types
• What is Arithmetic Line-Graph or Time-Series Graph?
• Diagrammatic and Graphic Presentation of Data

Chapter 6: Measures of Central Tendency: Arithmetic Mean

• Measures of Central Tendency in Statistics
• Arithmetic Mean: Meaning, Example, Types, Merits, and Demerits
• What is Simple Arithmetic Mean?
• Calculation of Mean in Individual Series | Formula of Mean
• Calculation of Mean in Discrete Series | Formula of Mean
• Calculation of Mean in Continuous Series | Formula of Mean
• Calculation of Arithmetic Mean in Special Cases
• Weighted Arithmetic Mean

Chapter 7: Measures of Central Tendency: Median and Mode

• Median(Measures of Central Tendency): Meaning, Formula, Merits, Demerits, and Examples
• Calculation of Median for Different Types of Statistical Series
• Calculation of Median in Individual Series | Formula of Median
• Calculation of Median in Discrete Series | Formula of Median
• Calculation of Median in Continuous Series | Formula of Median
• Graphical determination of Median
• Mode: Meaning, Formula, Merits, Demerits, and Examples
• Calculation of Mode in Individual Series | Formula of Mode
• Calculation of Mode in Discrete Series | Formula of Mode
• Grouping Method of Calculating Mode in Discrete Series | Formula of Mode
• Calculation of Mode in Continuous Series | Formula of Mode
• Calculation of Mode in Special Cases
• Calculation of Mode by Graphical Method
• Mean, Median and Mode| Comparison, Relationship and Calculation

Chapter 8: Measures of Dispersion

• Measures of Dispersion | Meaning, Absolute and Relative Measures of Dispersion
• Range | Meaning, Coefficient of Range, Merits and Demerits, Calculation of Range
• Calculation of Range and Coefficient of Range
• Interquartile Range and Quartile Deviation
• Partition Value | Quartiles, Deciles and Percentiles
• Quartile Deviation and Coefficient of Quartile Deviation: Meaning, Formula, Calculation, and Examples
• Quartile Deviation in Discrete Series | Formula, Calculation and Examples
• Quartile Deviation in Continuous Series | Formula, Calculation and Examples
• Mean Deviation: Coefficient of Mean Deviation, Merits, and Demerits
• Calculation of Mean Deviation for different types of Statistical Series
• Mean Deviation from Mean | Individual, Discrete, and Continuous Series
• Mean Deviation from Median | Individual, Discrete, and Continuous Series
• Standard Deviation: Meaning, Coefficient of Standard Deviation, Merits, and Demerits
• Standard Deviation in Individual Series
• Standard Deviation in Discrete Series
• Standard Deviation in Frequency Distribution Series
• Combined Standard Deviation: Meaning, Formula, and Example
• How to calculate Variance?
• Coefficient of Variation: Meaning, Formula and Examples
• Lorenz Curveb : Meaning, Construction, and Application

Chapter 9: Correlation

• Correlation: Meaning, Significance, Types and Degree of Correlation
• Methods of Measurements of Correlation
• Scatter Diagram Correlation | Meaning, Interpretation, Example
• Spearman's Rank Correlation Coefficient in Statistics
• Karl Pearson's Coefficient of Correlation | Assumptions, Merits and Demerits
• Karl Pearson's Coefficient of Correlation | Methods and Examples

Chapter 10: Index Number

• Index Number | Meaning, Characteristics, Uses and Limitations
• Methods of Construction of Index Number
• Unweighted or Simple Index Numbers: Meaning and Methods
• Methods of calculating Weighted Index Numbers
• Fisher's Index Number as an Ideal Method
• Fisher's Method of calculating Weighted Index Number
• Paasche's Method of calculating Weighted Index Number
• Laspeyre's Method of calculating Weighted Index Number
• Laspeyre's, Paasche's, and Fisher's Methods of Calculating Index Number
• Consumer Price Index (CPI) or Cost of Living Index Number: Construction of Consumer Price Index|Difficulties and Uses of Consumer Price Index
• Methods of Constructing Consumer Price Index (CPI)
• Wholesale Price Index (WPI) | Meaning, Uses, Merits, and Demerits
• Index Number of Industrial Production : Characteristics, Construction & Example
• Inflation and Index Number

Important Formulas in Statistics for Economics

• Important Formulas in Statistics for Economics | Class 11

What is Tabulation?

The systematic presentation of numerical data in rows and columns is known as Tabulation . It is designed to make presentation simpler and analysis easier. This type of presentation facilitates comparison by putting relevant information close to one another, and it helps in further statistical analysis and interpretation. One of the most important devices for presenting the data in a condensed and readily comprehensible form is tabulation. It aims to provide as much information as possible in the minimum possible space while maintaining the quality and usefulness of the data.

“Tabulation involves the orderly and systematic presentation of numerical data in a form designed to elucidate the problem under consideration.” – L.R. Connor

Objectives of Tabulation

The aim of tabulation is to summarise a large amount of numerical information into the simplest form. The following are the main objectives of tabulation:

• To make complex data simpler: The main aim of tabulation is to present the classified data in a systematic way. The purpose is to condense the bulk of information (data) under investigation into a simple and meaningful form.
• To save space: Tabulation tries to save space by condensing data in a meaningful form while maintaining the quality and quantity of the data.
• To facilitate comparison: It also aims to facilitate quick comparison of various observations by providing the data in a tabular form.
• To facilitate statistical analysis: Tabulation aims to facilitate statistical analysis because it is the stage between data classification and data presentation. Various statistical measures, including averages, dispersion, correlation, and others, are easily calculated from data that has been systematically tabulated.
• To provide a reference: Since data may be easily identifiable and used when organised in tables with titles and table numbers, tabulation aims to provide a reference for future studies.

Features of a Good Table

Tabulation is a very specialised job. It requires a thorough knowledge of statistical methods, as well as abilities, experience, and common sense. A good table must have the following characteristics:

• Title: The top of the table must have a title and it needs to be very appealing and attractive.
• Manageable Size: The table shouldn’t be too big or too small. The size of the table should be in accordance with its objectives and the characteristics of the data. It should completely cover all significant characteristics of data.
• Attractive: A table should have an appealing appearance that appeals to both the sight and the mind so that the reader can grasp it easily without any strain.
• Special Emphasis: The data to be compared should be placed in the left-hand corner of columns, with their titles in bold letters.
• Fit with the Objective: The table should reflect the objective of the statistical investigation.
• Simplicity: To make the table easily understandable, it should be simple and compact.
• Data Comparison: The data to be compared must be placed closely in the columns.
• Numbered Columns and Rows: When there are several rows and columns in a table, they must be numbered for reference.
• Clarity: A table should be prepared so that even a layman may make conclusions from it. The table should contain all necessary information and it must be self-explanatory.
• Units: The unit designations should be written on the top of the table, below the title. For example, Height in cm, Weight in kg, Price in ₹, etc. However, if different items have different units, then they should be mentioned in the respective rows and columns.
• Suitably Approximated: If the figures are large, then they should be rounded or approximated.
• Scientifically Prepared: The preparation of the table should be done in a systematic and logical manner and should be free from any kind of ambiguity and overlapping. 

Components of a Table

A table’s preparation is an art that requires skilled data handling. It’s crucial to understand the components of a good statistical table before constructing one. A table is created when all of these components are put together in a systematic order. In simple terms, a good table should include the following components:

1. Table Number:

Each table needs to have a number so it may be quickly identified and used as a reference.

• If there are many tables, they should be numbered in a logical order.
• The table number can be given at the top of the table or the beginning of the table title.
• The table is also identified by its location using subscripted numbers like 1.2, 2.1, etc. For instance, Table Number 3.1 should be seen as the first table of the third chapter.

Each table should have a suitable title. A table’s contents are briefly described in the title.

• The title should be simple, self-explanatory, and free from ambiguity.
• A title should be brief and presented clearly, usually below the table number.
• In certain cases, a long title is preferable for clarification. In these cases, a ‘Catch Title’ may be placed above the ‘Main Title’. For instance , the table’s contents might come after the firm’s name, which appears as a catch title.
• Contents of Title: The title should include the following information:  (i) Nature of data, or classification criteria (ii) Subject-matter (iii) Place to which the data relates  (iv) Time to which the data relates  (v) Source to which the data belongs  (vi) Reference to the data, if available.

3. Captions or Column Headings:

A column designation is given to explain the figures in the column at the top of each column in a table. This is referred to as a “Column heading” or “Caption”.

• Captions are used to describe the names or heads of vertical columns.
• To save space, captions are generally placed in small letters in the middle of the columns.

4. Stubs or Row Headings:

Each row of the table needs to have a heading, similar to a caption or column heading. The headers of horizontal rows are referred to as stubs. A brief description of the row headers may also be provided at the table’s left-hand top.

5. Body of Table:

The table’s most crucial component is its body, which contains data (numerical information).

• The location of any one figure or data in the table is fixed and determined by the row and column of the table.
• The columns and rows in the main body’s arrangement of numerical data are arranged from top to bottom.
• The size and shape of the main body should be planned in accordance with the nature of the figures and the purpose of the study.
• As the body of the table summarises the facts and conclusions of the statistical investigation, it must be ensured that the table does not have irrelevant information.

6. Unit of Measurement:

If the unit of measurement of the figures in the table (real data) does not change throughout the table, it should always be provided along with the title.

• However, these units must be mentioned together with stubs or captions if rows or columns have different units.
• If there are large figures, they should be rounded up and the rounding method should be stated.

7. Head Notes:

If the main title does not convey enough information, a head note is included in small brackets in prominent words right below the main title.

• A head-note is included to convey any relevant information.
• For instance, the table frequently uses the units of measurement “in million rupees,” “in tonnes,” “in kilometres,” etc. Head notes are also known as Prefatory Notes .

8. Source Note:

A source note refers to the place where information was obtained.

• In the case of secondary data, a source note is provided.
• Name of the book, page number, table number, etc., from which the data were collected should all be included in the source. If there are multiple sources, each one must be listed in the source note.
• If a reader wants to refer to the original data, the source note enables him to locate the data. Usually, the source note appears at the bottom of the table. For example, the source note may be: ‘Census of India, 2011’.
• Importance: A source note is useful for three reasons: -> It provides credit to the source (person or group), who collected the data; -> It provides a reference to source material that may be more complete; -> It offers some insight into the reliability of the information and its source.

9. Footnotes:

The footnote is the last part of the table. The unique characteristic of the data content of the table that is not self-explanatory and has not previously been explained is mentioned in the footnote.

• Footnotes are used to provide additional information that is not provided by the heading, title, stubs, caption, etc.
• When there are many footnotes, they are numbered in order.
• Footnotes are identified by the symbols *, @, £, etc.
• In general, footnotes are used for the following reasons: (i) To highlight any exceptions to the data (ii)Any special circumstances affecting the data; and (iii)To clarify any information in the data.

Merits of Tabular Presentation of Data

The following are the merits of tabular presentation of data:

• Brief and Simple Presentation: Tabular presentation is possibly the simplest method of data presentation. As a result, information is simple to understand. A significant amount of statistical data is also presented in a very brief manner.
• Facilitates Comparison: By grouping the data into different classes, tabulation facilitates data comparison.
• Simple Analysis: Analysing data from tables is quite simple. One can determine the data’s central tendency, dispersion, and correlation by organising the data as a table.
• Highlights Characteristics of the Data:  Tabulation highlights characteristics of the data. As a result of this, it is simple to remember the statistical facts.
• Cost-effective: Tabular presentation is a very cost-effective way to convey data. It saves time and space.
• Provides Reference: As the data provided in a tabular presentation can be used for other studies and research, it acts as a source of reference.

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Gdp up by 0.3% and employment up by 0.3% in the euro area, announcement.

Following recommendations for a harmonised European revision policy for national accounts and balance of payments , EU countries will carry out a benchmark revision of their national accounts estimates in 2024. The purpose of this benchmark revision is to implement changes introduced by the amended ESA 2010 regulation , and to incorporate new data sources and other methodological improvements. Most of the revised quarterly and annual country data are expected to be released by Eurostat between June and October 2024, and will be progressively integrated in European estimates. The impact of these revisions is expected to be limited, but still noticeable for some European aggregates and more pronounced for certain Member States. For further details, please consult the available documentation on Eurostat’s website .

GDP growth in the euro area and the EU

In the first quarter of 2024, seasonally adjusted GDP increased by 0.3% in both the euro area and the EU , compared with the previous quarter, according to an estimate published by Eurostat, the statistical office of the European Union . In the fourth quarter of 2023, GDP had declined by 0.1% in the euro area and had remained stable in the EU .

Compared with the same quarter of the previous year, seasonally adjusted GDP increased by 0.4% in the euro area and by 0.5% in the EU in the first quarter of 2024, after +0.2% in the euro area and +0.3% in the EU in the previous quarter.

During the first quarter of 2024, GDP in the United States increased by 0.3% compared to the previous quarter (after +0.8% in the fourth quarter of 2023). Compared with the same quarter of the previous year, GDP increased by 2.9% (after +3.1% in the previous quarter).

GDP growth by Member State

Malta (+1.3%) recorded the highest increase of GDP compared to the previous quarter, followed by Cyprus (+1.2%) and Croatia (+1.0%). Decreases were observed in Denmark (-1.8%), Estonia (-0.5%) and the Netherlands (‑0.1%).

GDP components and contributions to growth

GDP components evolved in the first quarter of 2024 as follows:

household final consumption expenditure increased by 0.2% in both the euro area and the EU (after +0.2% in the euro area and +0.3% in the EU in the previous quarter),

government final consumption expenditure was stable in the euro area and increased by 0.1 in the EU (after +0.6% in the euro area and +0.5% in the EU in the previous quarter),

gross fixed capital formation decreased by 1.5% in both the euro area and the EU (after +0.8% and +0.7% respectively),

exports increased by 1.4% in the euro area and by 1.0% in the EU (after +0.2% in the euro area and +0.4% in the EU ), and

imports decreased by 0.3% in the euro area and by 0.2% in the EU (after +0.6% and +0.5% respectively).

The contribution to GDP growth from:

household final consumption expenditure was positive for both the euro area and the EU (+0.1 percentage points – pp),

government final expenditure was negligible for both zones (+0.0 pp for both),

gross fixed capital formation was negative for both the euro area and the EU (-0.3 pp for both),

changes in inventories was negative for both euro area (-0.3 pp) and the EU (-0.1 pp), and

exports minus imports was positive for both the euro area (+0.9 pp) and the EU (+0.6 pp).

Employment growth in the euro area and EU

The number of employed persons increased by 0.3% in both the euro area and the EU in the first quarter of 2024, compared with the previous quarter, after +0.3% in the euro area and +0.2% in the EU in the fourth quarter of 2023.

Compared with the same quarter of the previous year, employment increased by 1.0% in the euro area and by 0.9% in the EU in the first quarter of 2024, after +1.2% in the euro area and +1.0% in the EU in the fourth quarter of 2023.

Hours worked increased by 0.3% in both the euro area and the EU in the first quarter of 2024, compared with the previous quarter. Compared with the same quarter of the previous year, the hours worked increased by 0.2% in the euro area and were stable in the EU .

These data provide a picture of labour input consistent with the output and income measure of national accounts.

Employment growth in Member States

In the first quarter of 2024, Romania (+2.4%), Malta (+1.4%) and Portugal (+1.1%) recorded the highest growth of employment in persons compared with the previous quarter. Decline of employment was recorded in Poland (-0.6%), Slovakia (-0.3%) and Sweden (-0.1%).

Employment levels in the euro area and EU

Based on seasonally adjusted figures, Eurostat estimates that in the first quarter of 2024, 218.0 million people were employed in the EU , of which 169.9 million were in the euro area .

Evolution of labour productivity in the euro area and EU

The combination of GDP and employment data allows an estimation of labour productivity .

In the first quarter of 2024, productivity based on persons decreased by 0.6% in the euro area and by 0.5% in the EU compared to the same quarter of the previous year.

Based on hours worked, productivity compared with the same quarter of the previous year decreased by 0.3% in the euro area and remained stable in the EU .

Overview on the evolution of main expenditure components

Notes for users.

The reliability of GDP and employment flash estimates was tested by dedicated working groups and revisions of subsequent estimates are continuously monitored. Further information can be found on Eurostat website .

With these estimates, euro area and EU employment and GDP figures for earlier quarters are revised.

Flash estimates of employment and GDP growth were published in News Release issued on 15 May 2024. They were based on a more limited data set than the one used for the present News Release and additionally, on preliminary estimates that have now been revised by some Member States. Revisions for the last quarter are highlighted in bold in the table below:

The European estimates published today include benchmark revisions from France and Sweden. All estimates presented in this release may be revised with the t+110 database update scheduled for 19 July 2024, which will reflect the impact of countries’ benchmark revisions as available.

Release schedule

This news release presents estimates for euro area and EU GDP and employment aggregates based on national accounts transmission from all Member States due after t+2 months.

A further estimation is done at around t+110 days after some countries transmit updated estimates.

To increase the timeliness of key indicators, Eurostat also publishes flash estimates for GDP (after around 30 and 45 days) and employment (after around 45 days). The flash estimates are based on estimates provided by most EU Member States on a voluntary basis.

Methods and definitions

European quarterly national accounts are compiled in accordance with the European System of Accounts 2010 (ESA 2010). They include key policy indicators on GDP and employment.

Gross domestic product (GDP) at market prices measures the production activity of resident producer units. Growth rates are based on chain-linked volumes.

Employment covers employees and self-employed working in resident production units (domestic concept). Employment flash estimates are limited to total employment in persons, but regular estimates also cover hours worked and industry breakdowns.

Labour productivity is compiled as the ratio of economic output (GDP, chain-linked volumes with reference year 2010) to labour input (total employment measured in persons or hours worked, for all industries, according to the domestic concept).

The method used for compilation of European GDP and employment estimates is the same as for previous releases.

Geographical information

Euro area (EA20): Belgium, Germany, Estonia, Ireland, Greece, Spain, France, Croatia, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Austria, Portugal, Slovenia, Slovakia and Finland.

European Union (EU27): Belgium, Bulgaria, Czechia, Denmark, Germany, Estonia, Ireland, Greece, Spain, France, Croatia, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, the Netherlands, Austria, Poland, Portugal, Romania, Slovenia, Slovakia, Finland and Sweden.

For more information

Website section on national accounts , notably information on European GDP and employment estimates

Database section on national accounts and Eurostat metadata on quarterly national accounts

Statistics Explained articles on measuring quarterly GDP and presentation of updated quarterly estimates

Country specific metadata

Country specific metadata on the recording of Ukrainian refugees in main aggregates of national accounts

European System of Accounts 2010

Euro indicators dashboard

Release calendar for Euro indicators

European Statistics Code of Practice

Get in touch

Media requests

Eurostat Media Support

Phone: (+352) 4301 33 408

E-mail: [email protected]

Further information on data

Thierry COURTEL (GDP)

E-mail: [email protected]

Jenny RUNESSON (Employment)

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