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

Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault, Second Edition addresses how Big Data fits within the existing information infrastructure and data warehousing systems. This is an essential topic as researchers and engineers increasingly need to deal with large and complex sets of data. Until data is gathered and placed into an existing framework or architecture, it cannot be used to its full potential. Drawing upon years of practical experience and using numerous examples and case studies from across industries, the authors explain where Big Data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together. Reviews the exponential growth of Big Data integration and applications across industries - from healthcare to finance Places new emphasis on end state architecture as a lens for understanding the architecture of Big Data Explains how Big Data fits within an existing systems environment, as well as the value of data transformation and redundancy Includes new chapters on data lakes, ponds, landing zones, IoT, edge computing, data modeling and taxonomies

• | Author: W.H. Inmon, Dan Linstedt, Mary Levins
• | Publisher: Academic Press
• | Publication Date: May 01, 2019
• | Number of Pages: 431 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 0128169168
• | ISBN-13: 9780128169162