erd case study examples with solutions pdf

Explaining an ER Diagram, With Steps and Use Cases

Sudip is a TOGAF Certified Solutions Architect with more than 15 years spent in the IT industry. He is now a full-time freelance technical writer and has contributed to several publications on various topics including the cloud, DevOps, SaaS, and cybersecurity. When not reading or writing, he is found playing a game of chess or in a squash court.

• Entity-Relationship Diagram
• Vertabelo Features

Get to know what an ER Diagram is through use cases and examples. Explore the notations for the essential components of an ERD.

Entity-relationship diagrams (ERDs) are used to visualize data and relationships among the entities of a system. At its core, an ER Diagram explains the logical structure and the flow of information within a data model. To do so, an entity-relationship diagram highlights entities, attributes , and relationships through predefined symbols for effective visualization of the architecture. Preparing an ERD is an essential first step towards designing a database, helping to analyze data flow and helping with due diligence of related system requirements.

When you Need an ER Diagram

An ER diagram is used to design database data models. If you are designing a new data model, preparing an ER Diagram helps with essential due diligence to capture and document system requirements. While in production, an ER diagram acts as a reference to improve database throughput , debug errors , and redesign architecture .

In addition to technical references, as ERDs are conceptual blueprint of the data flow within a system, they are also used to streamline business processes by identifying redundancies and bottlenecks within business entities.

In this article, we will go through a few ER diagram examples and how you can use Vertabelo to create ER diagrams to design efficient data models.

Objects in ER Diagrams

While there are several notations, the crow’s foot notation (also known as the information engineering notation or the IE notation) is prominently used in ER modeling due to its intuitive format and symbols. Let us delve into the representation of entities and relationships in crow’s foot notation to help model an ER diagram.

Entities represent data components within a database that could be living or non-living, real or abstract, so long as their data is stored in the database. Examples of entities include people, places, objects, events, or concepts. In ER diagrams, entities are usually depicted by rectangles, with the entity name at the top.

Client, City and Country Entities of a Data Model

An attribute is a description of the properties of an entity or relationship. For instance, the entity shipment could have attributes such as shipment ID ( id ), client_id , shipment time_created , billing_address , etc. In the crow’s foot notation, an attribute is represented as a line of text in the lower compartment of the corresponding entity’s rectangle.

A Snapshot Showing Various Attributes of the shipment Entity

Relationship

A relationship denotes how various entities interact with each other. For instance, in a database for a vehicle hiring service, a customer will form a relationship with the entity vehicle through the act of selecting . “Select” is, therefore, a relationship between the two entities.

The relationship between data in one table and data in another table is called cardinality . Specifically, the cardinality indicates the number of times one entity in a table can relate with the instances of another entity.

When drawing relationships in crow’s foot notation, there are two indicators: one for multiplicity (cardinality) while the other indicates whether a relationship is optional or mandatory. A mandatory relationship is shown by a line perpendicular to the relationship line, while an optional relationship is shown by an empty circle.

When drawing relationships in crow’s foot notation, there are two indicators: one for multiplicity (cardinality) while the other indicates whether a relationship is optional or mandatory. A mandatory relationship is shown by a line perpendicular to the relationship line, while an optional relationship is shown by an empty circle.

In data modeling, there are three types of cardinalities.

In a one-to-one association, one entity in a table can relate only once to an entity in another table. For instance, a customer can hire only one vehicle at a time, and a vehicle can be assigned to only one customer at a time.

In an entity-relationship diagram, one row in one table would correlate to only one row in another table. In the IE notation, a mandatory one-to-one relationship is represented by two lines perpendicular to the relationship line near both entity rectangles.

One-to-One Association With Mandatory Relationship

One-to-One Association With Optional Relationship

One-to-Many

A one-to-many relationship occurs when one instance of an entity can interact with multiple instances of another entity. For instance, one customer can hire several vehicles, while each vehicle can only be assigned to one customer at a time.

In the IE notation, a one-to-many relationship is represented by a single line at the end of the single instance, and a three-pronged crow’s-foot symbol facing the multiple instance rectangle.

One-to-Many Association With Mandatory Relationship

Many-to-Many

This type of cardinality occurs when multiple instances of one entity can relate with more than one instance of another set of entities. Imagine a scenario in which a customer could select multiple vehicles, and a vehicle could be leased by multiple customers within a certain time period. In the IE notation, a many-to-many relationship is depicted by crow’s feet at both ends of the relationship line.

Many-to-Many Association With Mandatory Relationship

Many-to-Many Association With Optional Relationship

While the above notations are in crow’s foot notation, there are a number of other ERD notation formats, the details of which can be found here .

Types of Data Models

There are three types of data models in ER modeling.

Conceptual and Logical Data Models 

The conceptual and logical data models describe how information is organized in a system regardless of the database used. The logical model specifies entities, attributes, and relationships between entities. It abstracts away from actual DBMS used in the implementation of the system.

Physical Data Model

The physical data model represents how the model will be built in the database. It shows the full table definition, including column names, column data types, table constraints, the primary key, the foreign keys, and the relationships between tables. The physical data model will be different for different RDBMS. For example, the data type for a given column may be different between MySQL and SQL Server.

This section appears incomplete. There is no explanation of what a conceptual model is (as opposed to logical). Also, the last sentence is incomplete. here .-->

How to Draw an ER Diagram

Let’s create an ER diagram for a data model using Vertabelo . Consider a simple scenario in which a client orders food at a restaurant. The client must purchase one or more menu items, while each menu item is served by one attendant.

1. First, identify the entities in your database. In this case, we have three entities: Client , Menu_Item , and Attendant .

2. The second step involves identifying the relationships between the selected entities.

• The Client is served a Menu_Item .
• The Attendant delivers the Menu_Item .

3. The third step involves identifying cardinalities .

• A Client can be assigned multiple Menu_Item s.
• An Attendant can only deliver one Menu_Item at a time before taking another order from the same Client (assumption) .

4. The fourth step is identifying entity attributes . Make sure that every attribute is mapped to only one entity; assign modifiers for those that belong to more than one.

Specify the primary key for each entity by using the most uniquely identifying attributes.

Setting the Attributes of an Entity Using the Vertabelo Property Editor

5. Once you have identified the entities, relationships, cardinalities, and attributes, you can now create your ER diagram. Here’s what our sample project will look like when designed using the crow’s foot (IE) notation.

Disclaimer: All the above diagrams were created using Vertabelo .

Data modeling challenges in the real world are often complex. Creating a precise ER diagram requires not only the right knowledge but also the right tools. Whether you are learning or designing a data model, Vertabelo acts as a great resource to your ERD designing needs. To find out more about Vertabelo features and how it can help, visit this article .

ER Diagram Example Use Cases

Let’s look at a few examples of the entity-relationship diagram to understand its use cases better.

Use Case: Data Model for a Freelancers Collective

You can find a detailed discussion of this ER diagram in A Data Model for a Freelancers Collective .

This model shows the logical structure that can be used in large freelance projects that require collaboration between distributed teams. Since the freelance world connects professionals in a wide range of fields with varying skill sets, you will need a tool to orchestrate the interactions among freelancers, teams, and clients. Let’s consider the Freelancer Collective platform as a project management solution that helps connect various actors to collaborate on a number of projects.

Our model is broken into four main subject areas: Freelancers , Customers & Projects , Teams , and Project Phases .

The Freelancers section includes all the information provided by freelancers when they register to use the application. The information relevant to our database includes the freelancer’s skills, skill level, and skill sets. We also need to understand the freelancer’s availability to be sure that they can deliver an assigned project.

The second focus area is Customers & Projects . Customers use the system to upload their projects and connect with freelancers. This section includes the customer , project , project_status_history , skill , and project_outcome tables. Customers have also registered to use the application, and the system extracts their details from a special form. Project details are revealed when the client posts a project.

The third section is for the teams . This subject area forms a team and assigns them a project based on the freelancer’s ability and skill sets. The team is the major entity for this section. Other tables in this section include team_member , in_charge , freelancer , phase_plan , and project .

The final section involves the Project phases . Some entities in this section have appeared in other subject areas, and these include freelancer , customer , project_outcome , and project . The new entities in this set include phase_history , phase_catalog , and phase_plan .

Relationships

When a client posts a project, the system checks for the skill requirements and the availability of freelancers. The system then creates a team of freelancers who will collaborate on the project, which is now divided into phases. This system works as a supervisor, looking for the best collective that will work on a project, and assigning different project phases to different freelancers depending on the availability and skill level.

Collectively, this is how the data model can look:

Use Case: Peer-to-Peer Lending Data Model

You can find a detailed discussion of this ER diagram in A Peer-to-Peer Lending Platform Data Model .

Peer-to-peer lending refers to the practice of multiple lenders and borrowers transacting through a common platform. A peer-to-peer lending platform here essentially acts as a liaison between the parties to enable the process of lending, while ensuring necessary compliance and maintaining data security of all parties.

Let’s understand the data model by considering a scenario.

The entities are the following:

• A borrower requests a loan of a specific amount through the peer-to-peer lending platform after submitting details of his credit score, default history, tax returns, etc. Additional details of the loan may include repayment duration and preferred interest rate window.
• The lender(s) register(s) on the platform by entering its respective financial details, including KYC, tax returns, etc. It also enters its lending preferences, including the loan duration, interest rate, amount, borrower credit score, etc.

The borrower asks for funding from an investor, who releases the funds through the loan fulfilment and repayment subsystem. This subsystem forms an associative relationship between the two entities.

The lending platform here essentially acts as the interface, connecting would-be investors with potential borrowers. This reduces the complexity of access to financing by allowing users to determine their own lending rates. The data model that can support this platform is outlined below:

An ER Diagram Is a Must

An ER diagram provides an easy way to represent your data model at a higher level of abstraction. With marked-up relationships among data sets, an ER diagram is perfect for process modeling and system debugging. In this article, we discussed the core concepts of ER modeling, with practical examples using Vertabelo for pragmatic experience. Whether you are learning or working on real-time data modeling, creating an ER diagram is a must.

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Home » Data Modeling / Database » Mastering ER Modeling: A Step-by-Step Guide with Real-World Examples (Part 2 of 5)

Mastering ER Modeling: A Step-by-Step Guide with Real-World Examples (Part 2 of 5)

• Posted on March 14, 2023
• / Under Data Modeling / Database

Refining Entity-Relationship Diagrams (ERDs) for Effective Database Design

Problem description: er modeling – a car rental company system.

A car rental company needs to create a database to manage their business operations. The company has a large fleet of cars that are rented out to customers for short-term and long-term rentals. The company has several branches in different locations, and each branch has its own fleet of cars.

The company wants to keep track of the cars that are available for rent, the customers who have rented the cars, the rental periods, and the charges for each rental. They also want to keep track of the maintenance schedules for each car and the maintenance activities that have been performed.

The company has the following requirements for their database:

• Cars can be rented out to customers for a specific rental period.
• A customer can rent multiple cars, and a car can be rented by multiple customers.
• The rental charges for each car should be calculated based on the rental period and any additional charges such as insurance or fuel charges.
• The company wants to keep track of the maintenance schedules for each car and the maintenance activities that have been performed.
• The company wants to be able to view reports on the usage of their cars, including the number of rentals, the rental periods, and the revenue generated.
• The company wants to be able to view reports on the maintenance activities performed on their cars, including the type of maintenance performed, the date it was performed, and the cost.
• The company wants to keep track of the customers who rent their cars, including their personal information such as name, address, phone number, and email address.
• The company wants to be able to view reports on their customers, including the number of rentals, the rental periods, and the revenue generated from each customer.

To meet these requirements, an Entity-Relationship (ER) diagram can be created to model the car rental system. The diagram will include entities such as Cars, Customers, Rentals, and Maintenance, and relationships such as Rental, Customer Rental, and Car Maintenance.

Step-by-Step Guide to Developing an ER Diagram for a Database

here’s a step-by-step guide to develop an ER diagram for a database:

• Identify the entities: Start by identifying the different entities that will be included in the database. These entities could be people, places, things, or concepts related to the domain of the database. For example, in a car rental system, the entities could include Cars, Customers, Rentals, and Maintenance.
• Determine the attributes: Next, determine the attributes of each entity. Attributes are characteristics or properties that describe the entity. For example, the attributes of a Car entity could include Make, Model, Year, and License Plate Number.
• Identify the relationships: After identifying the entities and their attributes, determine the relationships between the entities. Relationships are the connections or associations between entities. For example, the relationship between the Car and Rental entities is that a Car can be rented out for a specific rental period.
• Determine the cardinality: The cardinality describes the number of instances of one entity that can be associated with instances of another entity. For example, the cardinality between the Car and Rental entities could be one-to-many, meaning that one car can be rented out to many customers.
• Determine the degree of the relationship: The degree of the relationship refers to the number of entities involved in the relationship. For example, the relationship between the Car and Rental entities is a binary relationship, meaning that it involves only two entities.
• Create a preliminary diagram: Use the information gathered in the previous steps to create a preliminary ER diagram. This diagram should include the entities, attributes, relationships, cardinality, and degree of the relationship.
• Refine the diagram: Refine the ER diagram by reviewing it for accuracy, completeness, and consistency. Make any necessary adjustments or modifications to ensure that the diagram accurately represents the requirements of the database.
• Add constraints: Add any constraints to the diagram that will help ensure data integrity and consistency. Constraints are rules or conditions that restrict the data that can be entered into the database. For example, a constraint could be that a Car entity must have a valid license plate number.
• Finalize the diagram: Once the ER diagram has been refined and constraints have been added, finalize the diagram. The final diagram should accurately represent the database and its requirements.
• Generate the database: Using the finalized ER diagram, generate the database schema. The database schema defines the structure of the database, including the tables, columns, and relationships between them.

Understanding the Differences between Conceptual, Logical, and Physical Data Modeling

Here is an overview of what each stage entails:

• Conceptual data model: This stage is focused on understanding the high-level view of the data and the relationships between them. It is independent of any specific technology or database management system (DBMS). The main goal is to identify the main entities, their relationships, and their attributes. The outcome of this stage is a conceptual data model that is used to guide the development of a logical data model.
• Logical data model: This stage is focused on defining the data structures and relationships in detail. It includes a logical schema that maps to the data model concepts identified in the conceptual stage, using an entity-relationship diagram (ERD) or similar tool. The logical data model represents the requirements of the business in terms of data structure and relationships and is independent of the physical database design. The outcome of this stage is a logical data model that is used to guide the development of a physical data model.
• Physical data model: This stage is focused on translating the logical data model into a specific database management system, taking into consideration the performance, storage requirements, and technical constraints of the target DBMS. The physical data model describes the database objects, such as tables, columns, and indexes, as well as their data types, sizes, and constraints. The outcome of this stage is a physical data model that is used to create and implement the database.

In summary, the conceptual stage defines the data entities and their relationships at a high level, the logical stage defines the detailed data structures and relationships, and the physical stage maps the logical data model to a specific database technology, including performance and storage considerations.

Creating the Conceptual ERD from the Problem Description

The ERD includes four entities: Car, Customer, Rental, and Maintenance. Each entity has its attributes, such as car_id, model, make, year, daily_rate, fuel_type, is_available for Car entity, first_name, last_name, email, phone_number, and address for Customer entity, start_date, end_date, rental_rate, insurance_charge, fuel_charge for Rental entity, and type, description, cost, and maintenance_date for Maintenance entity.

The ERD also shows the relationships between the entities, including the Rental relationship between Car and Rental entities, Customer Rental relationship between Rental and Customer entities, and Car Maintenance relationship between Car and Maintenance entities.

Refine the Conceptual ERD to Logical ERD

The logical ERD includes a more formal, detailed notation emphasizing tables, columns, keys, and relationships. Specifically, the data types of the columns are presented. Besides, labels are added to the relationships (“rents,” “rented by,” and “requires”) to indicate the nature of each relationship.

Refine the Logical ERD to Physical ERD

The physical ERD is a ‘database schema diagram’ that provides details enough to implement the database in a specific DBMS. The naming of entities and columns is revised to:

• Support DBMS-specific syntax.
• Ensure the use of the non-reserved words (e.g. order -> purchase_order, desc -> description)
• Fit organizational-specific naming convention

The column ‘desc’ in the entity Maintenance is renamed to ‘description’.

Database Schema Generation: Transforming ERD into a Physical Schema

The database schema is a visual representation of the database structure that defines the organization of data in a relational database management system. The schema is created based on the entity-relationship diagram (ERD) that is used to model the relationships between different entities in a system.

In this case, the ERD was first refined into a logical ERD that defined the relationships between entities such as Cars, Customers, Rentals, and Maintenance, and their respective attributes. The logical ERD helped to establish the relationships and cardinality between the entities.

After refining the logical ERD, the next step was to generate a physical ERD that defines the actual database schema with all the necessary data types, primary and foreign keys, and any constraints. The physical ERD reflects the logical ERD but with more detail on how the data is stored in the database.

Based on the physical ERD, the SQL code was written to create the database schema with the appropriate tables, columns, and relationships between them. Each table in the schema represents an entity in the system, and the columns represent the attributes of that entity. The primary keys were defined to uniquely identify each record in the table, and foreign keys were used to establish relationships between tables.

CREATE TABLE Car ( car_id INT PRIMARY KEY, model VARCHAR(255), make VARCHAR(255), year INT, daily_rate DECIMAL(10, 2), fuel_type VARCHAR(255), is_available BOOLEAN ); CREATE TABLE Customer ( customer_id INT PRIMARY KEY, first_name VARCHAR(255), last_name VARCHAR(255), email VARCHAR(255), phone_number VARCHAR(255), address VARCHAR(255) ); CREATE TABLE Rental ( rental_id INT PRIMARY KEY, start_date DATE, end_date DATE, rental_rate DECIMAL(10, 2), insurance_charge DECIMAL(10, 2), fuel_charge DECIMAL(10, 2), car_id INT, customer_id INT, FOREIGN KEY (car_id) REFERENCES Car(car_id), FOREIGN KEY (customer_id) REFERENCES Customer(customer_id) ); CREATE TABLE Maintenance ( maintenance_id INT PRIMARY KEY, type VARCHAR(255), description TEXT, cost DECIMAL(10, 2), maintenance_date DATE, car_id INT, FOREIGN KEY (car_id) REFERENCES Car(car_id) );

The article discusses the process of refining entity-relationship diagrams (ERDs) to generate an effective database schema. The ERDs are refined from a conceptual level to a logical level and then to a physical level. The logical ERD establishes the relationships and cardinality between the entities, while the physical ERD defines the actual database schema with all the necessary data types, primary and foreign keys, and constraints.

The SQL code is then written based on the physical ERD to create the database schema with the appropriate tables, columns, and relationships. The article emphasizes the importance of refining ERDs for effective database design and provides insights into the process of generating a database schema from an ERD.

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Appendix B Sample ERD Exercises

Manufacturer.

A manufacturing company produces products. The following product information is stored: product name, product ID and quantity on hand. These products are made up of many components. Each component can be supplied by one or more suppliers. The following component information is kept: component ID, name, description, suppliers who supply them, and products in which they are used. Use Figure B.1 for this exercise.

Create an ERD to show how you would track this information.

Show entity names, primary keys, attributes for each entity, relationships between the entities and cardinality.

Assumptions

• A supplier can exist without providing components.
• A component does not have to be associated with a supplier.
• A component does not have to be associated with a product. Not all components are used in products.
• A product cannot exist without components.

Component( CompID , CompName, Description) PK=CompID

Product( ProdID, ProdName, QtyOnHand) PK=ProdID

Supplier(S uppID , SuppName) PK = SuppID

CompSupp( CompID, SuppID ) PK = CompID, SuppID

Build( CompID, ProdID , QtyOfComp) PK= CompID, ProdID

Car Dealership

Create an ERD for a car dealership. The dealership sells both new and used cars, and it operates a service facility (see Figure B.2). Base your design on the following business rules:

• A salesperson may sell many cars, but each car is sold by only one salesperson.
• A customer may buy many cars, but each car is bought by only one customer.
• A salesperson writes a single invoice for each car he or she sells.
• A customer gets an invoice for each car he or she buys.
• A customer may come in just to have his or her car serviced; that is, a customer need not buy a car to be classified as a customer.
• When a customer takes one or more cars in for repair or service, one service ticket is written for each car.
• The car dealership maintains a service history for each of the cars serviced. The service  records are referenced by the car’s serial number.
• A car brought in for service can be worked on by many mechanics, and each mechanic may work on many cars.
• A car that is serviced may or may not need parts (e.g., adjusting a carburetor or cleaning a fuel injector nozzle does not require providing new parts).

Database Design - 2nd Edition Copyright © 2014 by Adrienne Watt and Nelson Eng is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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Entity Relationship (ER) Diagram Model with DBMS Example

What is ER Diagram?

ER Diagram stands for Entity Relationship Diagram, also known as ERD is a diagram that displays the relationship of entity sets stored in a database. In other words, ER diagrams help to explain the logical structure of databases. ER diagrams are created based on three basic concepts: entities, attributes and relationships.

ER Diagrams contain different symbols that use rectangles to represent entities, ovals to define attributes and diamond shapes to represent relationships.

At first look, an ER diagram looks very similar to the flowchart. However, ER Diagram includes many specialized symbols, and its meanings make this model unique. The purpose of ER Diagram is to represent the entity framework infrastructure.

What is ER Model?

ER Model stands for Entity Relationship Model is a high-level conceptual data model diagram. ER model helps to systematically analyze data requirements to produce a well-designed database. The ER Model represents real-world entities and the relationships between them. Creating an ER Model in DBMS is considered as a best practice before implementing your database.

ER Modeling helps you to analyze data requirements systematically to produce a well-designed database. So, it is considered a best practice to complete ER modeling before implementing your database.

History of ER models

ER diagrams are visual tools that are helpful to represent the ER model. Peter Chen proposed ER Diagram in 1971 to create a uniform convention that can be used for relational databases and networks. He aimed to use an ER model as a conceptual modeling approach.

Why use ER Diagrams?

Here, are prime reasons for using the ER Diagram

• Helps you to define terms related to entity relationship modeling
• Provide a preview of how all your tables should connect, what fields are going to be on each table
• Helps to describe entities, attributes, relationships
• ER diagrams are translatable into relational tables which allows you to build databases quickly
• ER diagrams can be used by database designers as a blueprint for implementing data in specific software applications
• The database designer gains a better understanding of the information to be contained in the database with the help of ERP diagram
• ERD Diagram allows you to communicate with the logical structure of the database to users

Facts about ER Diagram Model

Now in this ERD Diagram Tutorial, let’s check out some interesting facts about ER Diagram Model:

• ER model allows you to draw Database Design
• It is an easy to use graphical tool for modeling data
• Widely used in Database Design
• It is a GUI representation of the logical structure of a Database
• It helps you to identifies the entities which exist in a system and the relationships between those entities

ER Diagrams Symbols & Notations

Entity Relationship Diagram Symbols & Notations mainly contains three basic symbols which are rectangle, oval and diamond to represent relationships between elements, entities and attributes. There are some sub-elements which are based on main elements in ERD Diagram. ER Diagram is a visual representation of data that describes how data is related to each other using different ERD Symbols and Notations.

Following are the main components and its symbols in ER Diagrams:

• Rectangles: This Entity Relationship Diagram symbol represents entity types
• Ellipses : Symbol represent attributes
• Diamonds: This symbol represents relationship types
• Lines: It links attributes to entity types and entity types with other relationship types
• Primary key: attributes are underlined
• Double Ellipses: Represent multi-valued attributes

Components of the ER Diagram

This model is based on three basic concepts:

• Relationships

ER Diagram Examples

For example, in a University database, we might have entities for Students, Courses, and Lecturers. Students entity can have attributes like Rollno, Name, and DeptID. They might have relationships with Courses and Lecturers.

WHAT IS ENTITY?

A real-world thing either living or non-living that is easily recognizable and nonrecognizable. It is anything in the enterprise that is to be represented in our database. It may be a physical thing or simply a fact about the enterprise or an event that happens in the real world.

An entity can be place, person, object, event or a concept, which stores data in the database. The characteristics of entities are must have an attribute, and a unique key. Every entity is made up of some ‘attributes’ which represent that entity.

Examples of entities:

• Person: Employee, Student, Patient
• Place: Store, Building
• Object: Machine, product, and Car
• Event: Sale, Registration, Renewal
• Concept: Account, Course

Notation of an Entity

An entity set is a group of similar kind of entities. It may contain entities with attribute sharing similar values. Entities are represented by their properties, which also called attributes. All attributes have their separate values. For example, a student entity may have a name, age, class, as attributes.

Example of Entities:

A university may have some departments. All these departments employ various lecturers and offer several programs.

Relationship

Relationship is nothing but an association among two or more entities. E.g., Tom works in the Chemistry department.

Entities take part in relationships. We can often identify relationships with verbs or verb phrases.

For example:

• You are attending this lecture
• I am giving the lecture
• Just loke entities, we can classify relationships according to relationship-types:
• A student attends a lecture
• A lecturer is giving a lecture.

Weak Entities

A weak entity is a type of entity which doesn’t have its key attribute. It can be identified uniquely by considering the primary key of another entity. For that, weak entity sets need to have participation.

In above ER Diagram examples, “Trans No” is a discriminator within a group of transactions in an ATM.

Let’s learn more about a weak entity by comparing it with a Strong Entity

It is a single-valued property of either an entity-type or a relationship-type.

For example, a lecture might have attributes: time, date, duration, place, etc.

An attribute in ER Diagram examples, is represented by an Ellipse

Cardinality

Defines the numerical attributes of the relationship between two entities or entity sets.

Different types of cardinal relationships are:

• One-to-One Relationships
• One-to-Many Relationships
• May to One Relationships
• Many-to-Many Relationships

1.One-to-one:

One entity from entity set X can be associated with at most one entity of entity set Y and vice versa.

Example: One student can register for numerous courses. However, all those courses have a single line back to that one student.

2.One-to-many:

One entity from entity set X can be associated with multiple entities of entity set Y, but an entity from entity set Y can be associated with at least one entity.

For example, one class is consisting of multiple students.

3. Many to One

More than one entity from entity set X can be associated with at most one entity of entity set Y. However, an entity from entity set Y may or may not be associated with more than one entity from entity set X.

For example, many students belong to the same class.

4. Many to Many:

One entity from X can be associated with more than one entity from Y and vice versa.

For example, Students as a group are associated with multiple faculty members, and faculty members can be associated with multiple students.

How to Create an Entity Relationship Diagram (ERD)

Now in this ERD Diagram Tutorial, we will learn how to create an ER Diagram. Following are the steps to create an ER Diagram:

Let’s study them with an Entity Relationship Diagram Example:

Step 1) Entity Identification

We have three entities

Step 2) Relationship Identification

We have the following two relationships

• The student is assigned a course
• Professor delivers a course

Step 3) Cardinality Identification

For them problem statement we know that,

• A student can be assigned multiple courses
• A Professor can deliver only one course

Step 4) Identify Attributes

You need to study the files, forms, reports, data currently maintained by the organization to identify attributes. You can also conduct interviews with various stakeholders to identify entities. Initially, it’s important to identify the attributes without mapping them to a particular entity.

Once, you have a list of Attributes, you need to map them to the identified entities. Ensure an attribute is to be paired with exactly one entity. If you think an attribute should belong to more than one entity, use a modifier to make it unique.

Once the mapping is done, identify the primary Keys. If a unique key is not readily available, create one.

For Course Entity, attributes could be Duration, Credits, Assignments, etc. For the sake of ease we have considered just one attribute.

Step 5) Create the ERD Diagram

A more modern representation of Entity Relationship Diagram Example

Best Practices for Developing Effective ER Diagrams

Here are some best practice or example for Developing Effective ER Diagrams.

• Eliminate any redundant entities or relationships
• You need to make sure that all your entities and relationships are properly labeled
• There may be various valid approaches to an ER diagram. You need to make sure that the ER diagram supports all the data you need to store
• You should assure that each entity only appears a single time in the ER diagram
• Name every relationship, entity, and attribute are represented on your diagram
• Never connect relationships to each other
• You should use colors to highlight important portions of the ER diagram
• ER Model in DBMS stands for an Entity-Relationship model
• The ER model is a high-level data model diagram
• ER diagrams are a visual tool which is helpful to represent the ER model
• ER diagrams in DBMS are blueprint of a database
• Entity relationship diagram DBMS displays the relationships of entity set stored in a database
• ER diagrams help you to define terms related to entity relationship modeling
• ER Model in DBMS is based on three basic concepts: Entities, Attributes & Relationships
• An entity can be place, person, object, event or a concept, which stores data in the database (DBMS)
• Relationship is nothing but an association among two or more entities
• A weak entity is a type of entity which doesn’t have its key attribute
• It is a single-valued property of either an entity-type or a relationship-type
• It helps you to defines the numerical attributes of the relationship between two entities or entity sets
• ER- Diagram DBMS is a visual representation of data that describe how data is related to each other
• While Drawing ER diagrams in DBMS, you need to make sure all your entities and relationships are properly labeled.
• Difference between Clustered and Non-clustered index
• Difference Between DDL and DML in DBMS
• Difference Between File System and DBMS
• Difference Between Primary Key and Foreign Key
• Row vs Column – Difference Between Them
• DBMS Tutorial PDF: Database Management Systems
• 10 BEST Database Management Software (DBMS) in 2024
• 60+ DBMS Interview Questions and Answers

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