Data Architecture: A Primer for the Data Scientist - A Primer for the Data Scientist (Paperback, 2nd edition)

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.

General

Imprint:	Academic Press Inc
Country of origin:	United States
Release date:	May 2019
First published:	2019
Authors:	William H. Inmon • Dan Linstedt • Mary Levins
Dimensions:	235 x 191 x 27mm (L x W x T)
Format:	Paperback
Pages:	431
Edition:	2nd edition
ISBN-13:	978-0-12-816916-2
Categories:	Books > Computing & IT > Social & legal aspects of computing > Human-computer interaction Books > Computing & IT > Applications of computing > Databases > General
LSN:	0-12-816916-8
Barcode:	9780128169162

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