Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data
- 2h 55m
- Chris Eaton, Dirk deRoos, George Lapis, Paul C. Zikopoulos, Thomas Deutsch
- McGraw-Hill/Osborne
- 2012
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.
- Learn how IBM hardens Hadoop for enterprise-class scalability and reliability
- Gain insight into IBM's unique in-motion and at-rest Big Data analytics platform
- Learn tips and tricks for Big Data use cases and solutions
- Get a quick Hadoop primer
About the Author
Paul C. Zikopoulos (Toronto, Canada) is a Database Specialist with the DB2 Sales Support team at IBM. He has written numerous magazine articles and books about DB2. Most recently, he co-authored the books A DBA's Guide to Databases on Linux (Syngress Media) and DB2 for Dummies (IDG Books). Zikopoulos is a DB2 Certified Advanced Technical Expert (DRDA and Cluster/EEE) and a DB2 Certified Solutions Expert (Business Intelligence and Database Administration).
In this Book
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Understanding Big Data—Analytics for Enterprise Class Hadoop and Streaming Data
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Foreword
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About this Book
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What Is Big Data? Hint—You’re a Part of It Every Day
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Why Is Big Data Important?
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Why IBM for Big Data?
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All About Hadoop—The Big Data Lingo Chapter
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InfoSphere BigInsights—Analytics for Big Data at Rest
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IBM InfoSphere Streams—Analytics for Big Data in Motion
