Understanding Big Data - Info and Reading Options
Analytics for Enterprise Class Hadoop and Streaming Data
By Paul C Zikopoulos, Chris Eaton, Dirk deRoos, Thomas Deutsch and George Lapis
"Understanding Big Data" was published by McGraw-Hill in 2012, it has 141 pages and the language of the book is English.
“Understanding Big Data” Metadata:
- Title: Understanding Big Data
- Authors: Paul C ZikopoulosChris EatonDirk deRoosThomas DeutschGeorge Lapis
- Language: English
- Number of Pages: 141
- Publisher: McGraw-Hill
- Publish Date: 2012
“Understanding Big Data” Subjects and Themes:
- Subjects: ➤ Database management - Data warehousing - Apache Hadoop (Computer file) - Electronic data processing - Distributed processing - File organization (Computer science) - Data mining - Apache Hadoop
Edition Specifications:
- Format: Paperback
- Pagination: xxxi, 141p
Edition Identifiers:
- The Open Library ID: OL25419058M - OL16797596W
- Online Computer Library Center (OCLC) ID: 760977087
- Library of Congress Control Number (LCCN): 2011410897
- ISBN-13: 9780071790536
- All ISBNs: 9780071790536
AI-generated Review of “Understanding Big Data”:
"Understanding Big Data" Table Of Contents:
- 1- The Big Deal about Big Data
- 2- What is Big Data? Hint: You're a Part of it Every Day
- 3- Why Is Big Data Important
- 4- Why IBM for Big Data
- 5- Big Data: From the Technology Perspective
- 6- All About Hadoop: The Big Data Lingo Chapter
- 7- InfoSphere BigInsights - Analytics for Big Data at Rest
- 8- IBM InfoSphere Streams - Analytics for Big Data in Motion
"Understanding Big Data" Description:
The Open Library:
"Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data-volume, variety, and velocity-are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide."--p. 4 of cover
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