Understanding Big Data

Understanding Big Data

Authors: Paul C Zikopoulos, Chris Eaton and Paul Zikopoulos

Published: October 2011

eISBN: 9780071790543 0071790543 | ISBN: 9780071790536

Contents

Foreword

Acknowledgments

About this Book

Part I: Big Data: From the Business Perspective

1 What Is Big Data? Hint: You’re a Part of it Every Day

Characteristics of Big Data

Data in the Warehouse and Data in Hadoop (It’s Not a Versus Thing)

Wrapping it Up

2 Why is Big Data Important?

When to Consider a Big Data Solution

Big Data Use Cases: Patterns for Big Data Deployment

3 Why IBM for Big Data?

Big Data Has No Big Brother: It’s Ready, but Still Young

What Can Your Big Data Partner Do for You?

A History of Big Data Innovation

Part II: Big Data: From the Technology Perspective

4 All About Hadoop: The Big Data Lingo Chapter

Just the Facts: The History of Hadoop

Components of Hadoop

Application Development in Hadoop

Getting Your Data into Hadoop

Other Hadoop Components

Wrapping It Up

5 InfoSphere BigInsights: Analytics for Big Data at Rest

Ease of Use: A Simple Installation Process

A Hadoop-Ready Enterprise-Quality File System: GPFS-SNC

Compression

Administrative Tooling

Security

Enterprise Integration

Improved Workload Scheduling: Intelligent Scheduler

Adaptive MapReduce

Data Discovery and Visualization: BigSheets

Advanced Text Analytics Toolkit

Machine Learning Analytics

Large-Scale Indexing

BigInsights Summed Up

6 IBM InfoSphere Streams: Analytics for Big Data in Motion

InfoSphere Streams Basics

How InfoSphere Streams Works

Enterprise Class