Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data

✍ Scribed by IBM, Paul Zikopoulos, Chris Eaton, Paul Zikopoulos

• Publisher: McGraw-Hill Osborne Media
• Year: 2011
• Tongue: English
• Leaves: 176
• Category: Library

✦ Synopsis

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

✦ Subjects

Информатика и вычислительная техника;Искусственный интеллект;Интеллектуальный анализ данных;