Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data
Published on 16. March 2012
Book
Paperback/Softback
176 pages
978-0-07-179053-6 (ISBN)
Description
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 reliabilityGain insight into IBM's unique in-motion and at-rest Big Data analytics platformLearn tips and tricks for Big Data use cases and solutionsGet a quick Hadoop primer
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 reliabilityGain insight into IBM's unique in-motion and at-rest Big Data analytics platformLearn tips and tricks for Big Data use cases and solutionsGet a quick Hadoop primer
More details
Language
English
Place of publication
United States
Publishing group
McGraw-Hill Education - Europe
Illustrations
15 Illustrations
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 10 mm
Weight
240 gr
ISBN-13
978-0-07-179053-6 (9780071790536)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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).
McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide
McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide
McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide
McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide
Content
Front Matter
PART 1: The Big Deal about Big Data
Chapter 1 What is Big Data? Hint: You're a Part of it Every Day
Chapter 2 Why Is Big Data Important
Chapter 3 Why IBM for Big Data
PART II: Big Data: From the Technology Perspective
Chapter 4 All About Hadoop: The Big Data Lingo Chapter
Chapter 5 InfoSphere BigInsights - Analytics for Big Data at Rest
Chapter 6 IBM InfoSphere Streams - Analytics for Big Data in Motion
PART 1: The Big Deal about Big Data
Chapter 1 What is Big Data? Hint: You're a Part of it Every Day
Chapter 2 Why Is Big Data Important
Chapter 3 Why IBM for Big Data
PART II: Big Data: From the Technology Perspective
Chapter 4 All About Hadoop: The Big Data Lingo Chapter
Chapter 5 InfoSphere BigInsights - Analytics for Big Data at Rest
Chapter 6 IBM InfoSphere Streams - Analytics for Big Data in Motion