Data Architecture: A Primer for the Data Scientist

A Primer for the Data Scientist

Nonfiction, Computers, Database Management, Application Software, Business Software, General Computing
Cover of the book Data Architecture: A Primer for the Data Scientist by W.H. Inmon, Daniel Linstedt, Mary Levins, Elsevier Science
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: W.H. Inmon, Daniel Linstedt, Mary Levins ISBN: 9780128169179
Publisher: Elsevier Science Publication: April 30, 2019
Imprint: Academic Press Language: English
Author: W.H. Inmon, Daniel Linstedt, Mary Levins
ISBN: 9780128169179
Publisher: Elsevier Science
Publication: April 30, 2019
Imprint: Academic Press
Language: English

Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a standard part of organizational decision-making. Throughout all this change, the basic principles that shape the architecture of data have remained the same. There remains a need for people to take a look at the "bigger picture" and to understand where their data fit into the grand scheme of things.

Data Architecture: A Primer for the Data Scientist, Second Edition addresses the larger architectural picture of how big data fits within the existing information infrastructure or data warehousing systems. This is an essential topic not only for data scientists, analysts, and managers but also for researchers and engineers who increasingly need to deal with large and complex sets of data. Until data are gathered and can be placed into an existing framework or architecture, they cannot be used to their full potential. Drawing upon years of practical experience and using numerous examples and case studies from across various industries, the authors seek to explain this larger picture into which big data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together.

  • New case studies include expanded coverage of textual management and analytics
  • New chapters on visualization and big data
  • Discussion of new visualizations of the end-state architecture
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a standard part of organizational decision-making. Throughout all this change, the basic principles that shape the architecture of data have remained the same. There remains a need for people to take a look at the "bigger picture" and to understand where their data fit into the grand scheme of things.

Data Architecture: A Primer for the Data Scientist, Second Edition addresses the larger architectural picture of how big data fits within the existing information infrastructure or data warehousing systems. This is an essential topic not only for data scientists, analysts, and managers but also for researchers and engineers who increasingly need to deal with large and complex sets of data. Until data are gathered and can be placed into an existing framework or architecture, they cannot be used to their full potential. Drawing upon years of practical experience and using numerous examples and case studies from across various industries, the authors seek to explain this larger picture into which big data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together.

More books from Elsevier Science

Cover of the book The Molecular Biology of Arrestins by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Viroids and Satellites by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Source Separation and Machine Learning by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Programmable Logic Controllers by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Strategies for Palladium-Catalyzed Non-directed and Directed C bond H Bond Functionalization by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Tribological Research and Design for Engineering Systems by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Fundamentals of Ecological Modelling by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Overcoming Information Poverty by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book The Developing Human Brain by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Advances in Agronomy by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Advances in Filament Yarn Spinning of Textiles and Polymers by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Cold Plasma in Food and Agriculture by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Gas Turbines by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Introduction to Satellite Remote Sensing by W.H. Inmon, Daniel Linstedt, Mary Levins
Cover of the book Material Selection for Thermoplastic Parts by W.H. Inmon, Daniel Linstedt, Mary Levins
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy