Data Architecture: A Primer for the Data Scientist A Primer for the Data Scientist

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  • Engels
  • Paperback
  • 9780128169162
  • 01 mei 2019
  • 431 pagina's
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Samenvatting

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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Taal
en
Bindwijze
Paperback
Oorspronkelijke releasedatum
01 mei 2019
Aantal pagina's
431
Illustraties
Nee

Betrokkenen

Hoofdauteur
William Inmon
Tweede Auteur
Daniel Linstedt
Co Auteur
Mary Levins
Hoofduitgeverij
Academic Press Inc

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Editie
2
Extra groot lettertype
Nee
Product breedte
191 mm
Product lengte
234 mm
Studieboek
Ja
Verpakking breedte
191 mm
Verpakking hoogte
235 mm
Verpakking lengte
234 mm
Verpakkingsgewicht
880 g

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EAN
9780128169162
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