Explore the latest full-text research PDFs, articles, conference papers, preprints and more on DATA ENGINEERING. Find methods information, sources, references or conduct a literature review on ...
Data Engineering papers/articles
Data Engineering papers/articles. It's quite common to find folks sharing papers on minor breakthroughs in areas like NLP, Computer Vision, Machine Learning, Deep Learning, and related fields here. We've carefully gathered a collection of papers focused on databases, distributed systems, and data in general.
[2102.11447] Data Engineering for Everyone
Data engineering is one of the fastest-growing fields within machine learning (ML). As ML becomes more common, the appetite for data grows more ravenous. But ML requires more data than individual teams of data engineers can readily produce, which presents a severe challenge to ML deployment at scale. Much like the software-engineering revolution, where mass adoption of open-source software ...
Home
Overview. Data Science and Engineering is a peer-reviewed, open access journal focusing on theoretical background and advanced engineering approaches in data science and engineering. Affiliated with the China Computer Federation (CCF) Technical Committee on Database (CCF TCDB). Provides in-depth coverage of advances in data science and data ...
Four Generations in Data Engineering for Data Science
In this article, available data engineering methods for data science applications will be classified. The main contribution of the article is a systematic overview of achievements in this research field till now (First, Second, and Third Generation), the open research questions in the present (mainly in the Third Generation) and the requirements that will have to be met for the future ...
PDF Software Engineering for Data Analytics
on, which I call data engineering for SE (DA4SE). Very few papers, only 13 out of 285 (4% of research papers at ASE 2016-2019) focused on im-proving SE for DA (Figure 1). In this article, I make the case that we, the SE research community, should expand its research scope to extend and adapt existing SE to meet the new demands of data-centric
Articles
Haiting Zhong. Wei He. Kun Zhao. Research Paper Open access 28 October 2022 Pages: 370 - 382. 1. 2. …. 5. Data Science and Engineering is a peer-reviewed, open access journal focusing on theoretical background and advanced engineering approaches in data science ...
PDF Greg Diamos Pete Warden Peter Mattson David Kanter
Figure 3: Ratio of ML research papers that rely on public versus private data sets per year. As the research output goes up, so does the usage of the open source data sets. 3 Data Engineering People have been working with large ML data sets for decades, but in many cases that work has been a sideline for exploring architectural or algorithmic ...
Data Engineering for Data Analytics: A ...
This paper provides a description and classification of such tasks into high-levels groups, namely data organization, data quality and feature engineering, and makes available four datasets and example analyses that exhibit a wide variety of these problems. Consider the situation where a data analyst wishes to carry out an analysis on a given dataset. It is widely recognized that most of the ...
PDF What About the Data? A Mapping Study on Data Engineering for AI Systems
The mapping study identified 25 papers that explain data engi-neering activities, tools, frameworks or architectures. By categoriz-ing them and summarizing their solutions and lesson learned, the paper creates an overview of the body of knowledge on data engi-neering for AI.
Data Engineering for Cognitive Economics
DOI 10.3386/w29378. Issue Date October 2021. Revision Date February 2024. Cognitive economics studies imperfect information and decision-making mistakes. A central scientific challenge is that these can't be identified in standard choice data. Overcoming this challenge calls for data engineering, in which new data forms are introduced to ...
DKE
Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these ...
Data-driven engineering design: A systematic review using scientometric
The yearly increase in the number of research articles on data-driven engineering design appears to be aligned with the growing trend of AI development, as shown by Wang et al. [41]. 3.2. RQ2: Main topics in DDED. Data-driven engineering design is a vast research area that covers diverse topics.
Economic Data Engineering by Andrew Caplin :: SSRN
Economic data engineering deliberately designs novel forms of data to solve fundamental identification problems associated with economic models of choice. I outline three diverse applications: to the economics of information; to life-cycle employment, earnings, and spending; and to public policy analysis. In all three cases one and the same ...
Software Engineering for Data Analytics
Abstract: We are at an inflection point where software engineering meets the data-centric world of big data, machine learning, and artificial intelligence. In this article, I summarize findings from studies of professional data scientists and discuss my perspectives on open research problems to improve data-centric software development.
Data-Centric Engineering
Data-Centric Engineering (DCE) is a peer-reviewed open-access journal dedicated to the transformative impact of data science for research and practice across all areas of engineering. Articles explore the benefits of data science methods and models for improving the reliability, resilience, safety, efficiency and usability of engineered systems.
Azure Data Engineering Cookbook: Design and implement batch and
Data engineering is one of the faster growing job areas as Data Engineers are the ones who ensure that the data is extracted, provisioned and the data is of the highest quality for data analysis. This book uses various Azure services to implement and maintain infrastructure to extract data from multiple sources, and then transform and load it ...
Data science: a game changer for science and innovation
This paper shows data science's potential for disruptive innovation in science, industry, policy, and people's lives. We present how data science impacts science and society at large in the coming years, including ethical problems in managing human behavior data and considering the quantitative expectations of data science economic impact. We introduce concepts such as open science and e ...
Electronics
To solve this problem, this paper takes mechanical engineering as the research object, and proposes a new machine-learning-driven GPA prediction approach to evaluate the academic performance of engineering students by incorporating psychological evaluation data into basic course scores.
PDF Snowflake for Data Engineering
WHITE PAPER 2 DATA PIPELINE PERFORMANCE IS THE FOUNDATION OF A DATA-DRIVEN ORGANIZATION Data pipelines are the lifeblood of the modern ... Gartner Research Data Engineering Is Critical to Driving Data and Analytics Success, December 18, 2019 1. WHITE PAPER 3 4 Many tools and custom code Diverse skill sets
Residual attention temporal recurrent network for fault diagnosis of
School of Mechanical Engineering, Southeast University, Nanjing, 211189, PR China ... a fault diagnosis framework with self-supervised sample generation learning is explored in this paper. First, a small amount of labeled data is utilized to self-supervise the generation of new samples with similar semantics in adversarial generation modeling ...
Data, Engineering and Applications
About this book. The book contains select proceedings of the 3rd International Conference on Data, Engineering, and Applications (IDEA 2021). It includes papers from experts in industry and academia that address state-of-the-art research in the areas of big data, data mining, machine learning, data science, and their associated learning systems ...
[2405.07762] A method for supervoxel-wise association studies of age
The study of associations between an individual's age and imaging and non-imaging data is an active research area that attempts to aid understanding of the effects and patterns of aging. In this work we have conducted a supervoxel-wise association study between both volumetric and tissue density features in coronary computed tomography angiograms and the chronological age of a subject, to ...
Matchmaking for Industrial Symbiosis: a digital tool for the
Effective waste management is crucial for sustainable industrial operations. This paper introduces a state-of-the-art digital tool designed for the circular economy. Primarily it pinpoints and quantifies symbiotic possibilities between industries with liquid waste streams, emphasising the most lucrative inter-industry connections. In practice, the tool takes in data such as waste stream ...
Exploring the Relationship Between Early Life Exposures and the
Abstract Background: Epidemiological research commonly investigates single exposure-outcome relationships, while childrens experiences across a variety of early lifecourse domains are intersecting. To design realistic interventions, epidemiological research should incorporate information from multiple risk exposure domains to assess effect on health outcomes. In this paper we identify ...
2024-01-2750: Evaluation of the Full-Frontal Crash Regulation for the
Background: The Indian automobile industry, including the auto component industry, is a significant part of the country's economy and has experienced growth over the years.India is now the world's 3 rd largest passenger car market and the world's second-largest two-wheeler market. Along with the boon, the bane of road accident fatalities is also a reality that needs urgent attention, as ...
Data-driven Discrete Simulation-based Dynamic Modeling and ...
Low-carbon manufacturing is an inevitable requirement for the green transformation of enterprises. For batch hobbing, continuous improvement of process parameters is an important way to achieve low-carbon optimization under the constraints of limited data and time-varying machining configurations. This is the research gap that needs to be filled. Therefore, in this paper, a dynamic modeling ...
COMMENTS
Explore the latest full-text research PDFs, articles, conference papers, preprints and more on DATA ENGINEERING. Find methods information, sources, references or conduct a literature review on ...
Data Engineering papers/articles. It's quite common to find folks sharing papers on minor breakthroughs in areas like NLP, Computer Vision, Machine Learning, Deep Learning, and related fields here. We've carefully gathered a collection of papers focused on databases, distributed systems, and data in general.
Data engineering is one of the fastest-growing fields within machine learning (ML). As ML becomes more common, the appetite for data grows more ravenous. But ML requires more data than individual teams of data engineers can readily produce, which presents a severe challenge to ML deployment at scale. Much like the software-engineering revolution, where mass adoption of open-source software ...
Overview. Data Science and Engineering is a peer-reviewed, open access journal focusing on theoretical background and advanced engineering approaches in data science and engineering. Affiliated with the China Computer Federation (CCF) Technical Committee on Database (CCF TCDB). Provides in-depth coverage of advances in data science and data ...
In this article, available data engineering methods for data science applications will be classified. The main contribution of the article is a systematic overview of achievements in this research field till now (First, Second, and Third Generation), the open research questions in the present (mainly in the Third Generation) and the requirements that will have to be met for the future ...
on, which I call data engineering for SE (DA4SE). Very few papers, only 13 out of 285 (4% of research papers at ASE 2016-2019) focused on im-proving SE for DA (Figure 1). In this article, I make the case that we, the SE research community, should expand its research scope to extend and adapt existing SE to meet the new demands of data-centric
Haiting Zhong. Wei He. Kun Zhao. Research Paper Open access 28 October 2022 Pages: 370 - 382. 1. 2. …. 5. Data Science and Engineering is a peer-reviewed, open access journal focusing on theoretical background and advanced engineering approaches in data science ...
Figure 3: Ratio of ML research papers that rely on public versus private data sets per year. As the research output goes up, so does the usage of the open source data sets. 3 Data Engineering People have been working with large ML data sets for decades, but in many cases that work has been a sideline for exploring architectural or algorithmic ...
This paper provides a description and classification of such tasks into high-levels groups, namely data organization, data quality and feature engineering, and makes available four datasets and example analyses that exhibit a wide variety of these problems. Consider the situation where a data analyst wishes to carry out an analysis on a given dataset. It is widely recognized that most of the ...
The mapping study identified 25 papers that explain data engi-neering activities, tools, frameworks or architectures. By categoriz-ing them and summarizing their solutions and lesson learned, the paper creates an overview of the body of knowledge on data engi-neering for AI.
DOI 10.3386/w29378. Issue Date October 2021. Revision Date February 2024. Cognitive economics studies imperfect information and decision-making mistakes. A central scientific challenge is that these can't be identified in standard choice data. Overcoming this challenge calls for data engineering, in which new data forms are introduced to ...
Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these ...
The yearly increase in the number of research articles on data-driven engineering design appears to be aligned with the growing trend of AI development, as shown by Wang et al. [41]. 3.2. RQ2: Main topics in DDED. Data-driven engineering design is a vast research area that covers diverse topics.
Economic data engineering deliberately designs novel forms of data to solve fundamental identification problems associated with economic models of choice. I outline three diverse applications: to the economics of information; to life-cycle employment, earnings, and spending; and to public policy analysis. In all three cases one and the same ...
Abstract: We are at an inflection point where software engineering meets the data-centric world of big data, machine learning, and artificial intelligence. In this article, I summarize findings from studies of professional data scientists and discuss my perspectives on open research problems to improve data-centric software development.
Data-Centric Engineering (DCE) is a peer-reviewed open-access journal dedicated to the transformative impact of data science for research and practice across all areas of engineering. Articles explore the benefits of data science methods and models for improving the reliability, resilience, safety, efficiency and usability of engineered systems.
Data engineering is one of the faster growing job areas as Data Engineers are the ones who ensure that the data is extracted, provisioned and the data is of the highest quality for data analysis. This book uses various Azure services to implement and maintain infrastructure to extract data from multiple sources, and then transform and load it ...
This paper shows data science's potential for disruptive innovation in science, industry, policy, and people's lives. We present how data science impacts science and society at large in the coming years, including ethical problems in managing human behavior data and considering the quantitative expectations of data science economic impact. We introduce concepts such as open science and e ...
To solve this problem, this paper takes mechanical engineering as the research object, and proposes a new machine-learning-driven GPA prediction approach to evaluate the academic performance of engineering students by incorporating psychological evaluation data into basic course scores.
WHITE PAPER 2 DATA PIPELINE PERFORMANCE IS THE FOUNDATION OF A DATA-DRIVEN ORGANIZATION Data pipelines are the lifeblood of the modern ... Gartner Research Data Engineering Is Critical to Driving Data and Analytics Success, December 18, 2019 1. WHITE PAPER 3 4 Many tools and custom code Diverse skill sets
School of Mechanical Engineering, Southeast University, Nanjing, 211189, PR China ... a fault diagnosis framework with self-supervised sample generation learning is explored in this paper. First, a small amount of labeled data is utilized to self-supervise the generation of new samples with similar semantics in adversarial generation modeling ...
About this book. The book contains select proceedings of the 3rd International Conference on Data, Engineering, and Applications (IDEA 2021). It includes papers from experts in industry and academia that address state-of-the-art research in the areas of big data, data mining, machine learning, data science, and their associated learning systems ...
The study of associations between an individual's age and imaging and non-imaging data is an active research area that attempts to aid understanding of the effects and patterns of aging. In this work we have conducted a supervoxel-wise association study between both volumetric and tissue density features in coronary computed tomography angiograms and the chronological age of a subject, to ...
Effective waste management is crucial for sustainable industrial operations. This paper introduces a state-of-the-art digital tool designed for the circular economy. Primarily it pinpoints and quantifies symbiotic possibilities between industries with liquid waste streams, emphasising the most lucrative inter-industry connections. In practice, the tool takes in data such as waste stream ...
Abstract Background: Epidemiological research commonly investigates single exposure-outcome relationships, while childrens experiences across a variety of early lifecourse domains are intersecting. To design realistic interventions, epidemiological research should incorporate information from multiple risk exposure domains to assess effect on health outcomes. In this paper we identify ...
Background: The Indian automobile industry, including the auto component industry, is a significant part of the country's economy and has experienced growth over the years.India is now the world's 3 rd largest passenger car market and the world's second-largest two-wheeler market. Along with the boon, the bane of road accident fatalities is also a reality that needs urgent attention, as ...
Low-carbon manufacturing is an inevitable requirement for the green transformation of enterprises. For batch hobbing, continuous improvement of process parameters is an important way to achieve low-carbon optimization under the constraints of limited data and time-varying machining configurations. This is the research gap that needs to be filled. Therefore, in this paper, a dynamic modeling ...