Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault [Audiobook] download free by William H. Inmon

Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault Audiobook download free by William H. Inmon
  • Listen audiobook: Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault
  • Author: William H. Inmon
  • Release date: 2015/12/16
  • Publisher: ELSEVIER SCIENCE & TECHNOLOGY
  • Language: English
  • Genre or Collection: Computing
  • ISBN: 9780128020449
  • Rating: 9.65 of 10
  • Votes: 130
  • Review by: Reece Tanaka
  • Review rating: 7.62 of 10
  • Review Date: 2018/9/6
  • Duration: 4H43M51S in 256 kbps (75.6 MB)
  • Date of creation of the audiobook: 2018-08-13
  • You can listen to this audiobook in formats: MP3, MPEG4, FLAC, MOD, WAV, MPEG-4 ALS, WMA, Vorbis (compression TZ, BZ2, RAR, ZIP, EML, TBZ)
  • Total pages original book: 378
  • Includes a PDF summary of 33 pages
  • Duration of the summary (audio): 26M16S (6.6 MB)
  • Description or summary of the audiobook: 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 DataUnderstand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data
  • Other categories, genre or collection: Databases, Information Retrieval, Database Programming, Data Warehousing, Enterprise Software
  • Download servers: Uploaded, Google Drive, CmisSync, FreakShare, BitShare. Compressed in TZ, BZ2, RAR, ZIP, EML, TBZ
  • Format: Paperback
  • Approximate value: 63.25 USD
  • Dimensions: 191x235x22.86mm
  • Weight: 770g
  • Printed by: Morgan Kaufmann Publishers In
  • Published in: San Francisco, United States

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