Lybrary.com: ebooks and download videos Search All  Title  Author 
Home / Nonfiction / Computers / Database Management / Data Warehousing

Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault

$59.95
| £48.99 | €56.73 | Ca$81.68 | Au$80.26
by W. H. Inmon & Dan Linstedt
What is this?DRM-EPUB by download  |  $59.95
What is this?DRM-PDF by download  |  $59.95
add to wish list
Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault by W. H. Inmon & Dan Linstedt

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

To view this DRM protected ebook on your desktop or laptop you will need to have Adobe Digital Editions installed. It is a free software. We also strongly recommend that you sign up for an AdobeID at the Adobe website. For more details please see FAQ 1&2. To view this ebook on an iPhone, iPad or Android mobile device you will need the Adobe Digital Editions app, or BlueFire Reader or Txtr app. These are free, too. For more details see this article.


SHARE  Share by Email  Share on Facebook  Share on Twitter  Share on Linked In  Share on Delicious
or call in the US toll free 1-888-866-9150 product ID: 656760

Ebook Details
Pages: 378
Size: 61.8 MB
Publisher: Morgan Kaufmann
Date published:   2014
ISBN: 2370006344827 (DRM-EPUB)
9780128020913 (DRM-PDF)

DRM Settings
Copying:allowed
Printing:allowed
Read Aloud:  not allowed

This product is listed in the following category:

Nonfiction > Computers > Database Management > Data Warehousing

These authors have products in the following categories:

Nonfiction > Computers > Database Management
Nonfiction > Computers > Database Management > Data Warehousing
Nonfiction > Computers > Data Modeling & Design

If you find anything wrong with this product listing, perhaps the description is wrong, the author is incorrect, or it is listed in the wrong category, then please contact us. We will promptly address your feedback.

Submit 5 page SummaryWhat is this?

03/25/2017
© 2017 Lybrary.com