Data Architecture: A Primer for the Data Scientist: A Primer for the Data Scientist, 2nd Edition


Data Architecture: A Primer for the Data Scientist: A Primer for the Data Scientist 2nd Edition
By 作者:W.H. Inmon (Author), Daniel Linstedt (Author), Mary Levins (Author)
Publisher Finelybook 出版社 : Academic Press; 2nd edition (May 15, 2019)
Language : English
pages 页数: 431 pages
ISBN-10 : 0128169168
ISBN-13 : 9780128169162
The Book Description robot was collected from Amazon and arranged by Finelybook
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
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