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Data Architecture: A Primer for the Data Scientist

Big Data, Data Warehouse and Data Vault

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 existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can't be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist.
Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You'll be able to:
Turn textual information into a form that can be analyzed by standard tools.
Make the connection between analytics and Big Data
Understand how Big Data fits within an existing systems environment
Conduct analytics on repetitive and non-repetitive data
Discusses the value in Big Data that is often overlooked, non-repetitive data, and why there is significant business value in using it
Shows how to turn textual information into a form that can be analyzed by standard tools.
Explains how Big Data fits within an existing systems environment
Presents new opportunities that are afforded by the advent of Big Data
Demystifies the murky waters of repetitive and non-repetitive data in Big Data
Portrait
Dan Linstedt is founder and principle of Empowered Holdings, LLC - a holding company for LearnDataVault.com, and RapidGenDS.com. LearnDataVault.com and a is a world-renowned expert in Data Warehousing and Business Intelligence. He has 20+ years of experience in the IT industry, and has worked with companies like Nike, PepsiCo, Amex, and Visa. His experience extends through data modeling, process design to ETL/ELT performance and tuning. He has a background in SEI/CMMI Level 5, and has contributed architecture efforts to petabyte scale data warehouses offers high quality on-line training and consulting services for Data Vault. He is the inventor and founder of the Data Vault modeling and methodology.
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Beschreibung

Produktdetails


Einband Taschenbuch
Seitenzahl 378
Erscheinungsdatum 26.01.2015
Sprache Englisch
ISBN 978-0-12-802044-9
Reihe Morgan Kaufmann
Verlag Elsevier LTD, Oxford
Maße (L/B/H) 231/186/27 mm
Gewicht 781
Buch (Taschenbuch, Englisch)
Fr. 68.90
inkl. gesetzl. MwSt.
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