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Verlag: Morgan Kaufmann Publishers, 2014
ISBN 10: 012802044X ISBN 13: 9780128020449
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
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In den WarenkorbPaperback. Zustand: Near Fine. First Edition. CLEAN near fine 2015 paperback.
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Verlag: Morgan Kaufmann 2014-11-26, 2014
ISBN 10: 012802044X ISBN 13: 9780128020449
Sprache: Englisch
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In den WarenkorbZustand: New. pp. 450.
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In den WarenkorbPaperback. Zustand: Brand New. 1st edition. 378 pages. 9.50x7.50x0.75 inches. In Stock.
Verlag: Academic Press 2019-06-01, 2019
ISBN 10: 0128169168 ISBN 13: 9780128169162
Sprache: Englisch
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In den WarenkorbZustand: As New. Unread book in perfect condition.
Verlag: Elsevier Science Publishing Co Inc, US, 2019
ISBN 10: 0128169168 ISBN 13: 9780128169162
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: New. 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.
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In den WarenkorbPaperback. Zustand: Brand New. 2nd edition. 450 pages. 9.25x7.50x0.83 inches. In Stock.
Verlag: Elsevier Science Publishing Co Inc, US, 2019
ISBN 10: 0128169168 ISBN 13: 9780128169162
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: New. 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.
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In den WarenkorbZustand: New. pp. 450.
Verlag: Elsevier Science & Technology|Academic Press, 2019
ISBN 10: 0128169168 ISBN 13: 9780128169162
Sprache: Englisch
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In den WarenkorbZustand: New. 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 architec.
Verlag: Elsevier Science Publishing Co Inc, 2019
ISBN 10: 0128169168 ISBN 13: 9780128169162
Sprache: Englisch
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In den WarenkorbZustand: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher.
Verlag: Elsevier Science Publishing Co Inc, US, 2019
ISBN 10: 0128169168 ISBN 13: 9780128169162
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: New. 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.
Verlag: Elsevier Science Publishing Co Inc, US, 2019
ISBN 10: 0128169168 ISBN 13: 9780128169162
Sprache: Englisch
Anbieter: Rarewaves.com UK, London, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: New. 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.
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In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the.