Harness The Power Of Big Data The Ibm Big Data Platform
The IBM Big Data Platform
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Boost your Big Data IQ! Gain insight into how to govern and consume IBM’s unique in-motion and at-rest Big Data analytic capabilities
Big Data represents a new era of computing—an inflection point of opportunity where data in any format may be explored and utilized for breakthrough insights—whether that data is in-place, in-motion, or at-rest. IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is infusing open source Big Data technologies with IBM innovation that manifest in a platform capable of "changing the game."
The four defining characteristics of Big Data—volume, variety, velocity, and veracity—are discussed. You’ll understand how IBM is fully committed to Hadoop and integrating it into the enterprise. Hear about how organizations are taking inventories of their existing Big Data assets, with search capabilities that help organizations discover what they could already know, and extend their reach into new data territories for unprecedented model accuracy and discovery.
In this book you will also learn not just about the technologies that make up the IBM Big Data platform, but when to leverage its purpose-built engines for analytics on data in-motion and data at-rest. And you’ll gain an understanding of how and when to govern Big Data, and how IBM’s industry-leading InfoSphere integration and governance portfolio helps you understand, govern, and effectively utilize Big Data. Industry use cases are also included in this practical guide.
|Titel:||Harness The Power Of Big Data The Ibm Big Data Platform|
|auteur:||Corrigan, David; Giles, James; Deutsch, Thomas; Parasuraman, Krishnan; deRoos, Dirk; Zikopoulos, Paul|
|Uitgever:||Mcgraw-hill Education - Europe|
|Afmetingen:||226 x 224 x 15|
Paul C. Zikopoulos, B.A., M.B.A., is the Director of Technical Professionals for IBM Software Group’s Information Management division and additionally leads the World-Wide Competitive Database and Big Data Technical Sales Acceleration teams.
Dirk deRoos, B.Sc., B.A., is IBM’s World-Wide Technical Sales Leader for IBM InfoSphere BigInsights. He spent the past two years helping customers with BigInsights and Apache Hadoop, identifying architecture fit, and advising early stage projects in dozens of customer engagements.
Krishnan Parasuraman, B.Sc., M.Sc., is part of IBM’s Big Data industry solutions team and serves as the CTO for Digital Media. In his role, Krishnan works very closely with customers in an advisory capacity, driving Big Data solution architectures and best practices for the management of Internet-scale analytics.
Thomas Deutsch, B.A, M.B.A., is a Program Director for IBM’s Big Data team. He played a formative role in the transition of Hadoop-based technology from IBM Research to IBM Software Group and continues to be involved with IBM Research around Big Data.
David Corrigan, B.A., M.B.A., is currently the Director of Product Marketing for IBM’s InfoSphere portfolio, which is focused on managing trusted information. His primary focus is driving the messaging and strategy for the InfoSphere portfolio of information integration, data quality, master data management (MDM), data lifecycle management, and data privacy and security.
James Giles, BSEE, B.Math, MSEE, Ph.D., is an IBM Distinguished Engineer and currently a Senior Development Manager for the IBM InfoSphere BigInsights and IBM InfoSphere Streams Big Data products.
Chapter 1: What is Big Data?
Chapter 2: Applying Big Data To Solve Problems: A Sampling Of Use Cases
Chapter 3: Boost Your Big Data IQ: The IBM Big Data Platform
PART II: Analytics for Big Data at Rest
Chapter 4: A Big Data Platform for High Performance Operational and Deep Analytics: IBM PureData Systems
Chapter 5: IBM’s Enterprise Hadoop: InfoSphere BigInsights
PART III: Analytics for Big Data in Motion
Chapter 6: Real Time Analytical Processing with InfoSphere Streams
PART IV: Unlocking Big Data
Chapter 7: Data Exploration – Powered by Vivisimo Technology
PART V: Big Data Analytic Accelerators
Chapter 8: Differentiate Yourself with Text Analytics
Chapter 9: The IBM Big Data Accelerators
PART VI: Integration and Governance in a Big Data World
Chapter 10: To Govern or Not to Govern: Governance in a Big Data World
Chapter 11: Integrating Big Data in the Enterprise