IBM Infosphere: A Platform for Big Data Governance and Process Data Governance

ISBN-10: 1583473823
ISBN-13: 9781583473825
Edition: 2013
Authors: Sunil Soares
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Description: Written by a leading expert in the field of information governance, this book is the only available that focuses specifically on IBM solutions and the convergence of two major trends in information management today: big data and information  More...

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Book details

List price: $16.95
Copyright year: 2013
Publisher: Independent Pub Group
Binding: Paperback
Pages: 112
Size: 5.75" wide x 8.75" long x 0.25" tall
Weight: 0.330
Language: English

Written by a leading expert in the field of information governance, this book is the only available that focuses specifically on IBM solutions and the convergence of two major trends in information management today: big data and information governance. Nontechnical in nature and geared toward business audiences responsible for the analytics of big data, the book provides a big data governance framework with three dimensions: big data types, information governance disciplines, and industries and functions. Practitioners can use the knowledge presented in this book to understand big data support across the IBM InfoSphere portfolio, including DataStage, Streams, QualityStage, MDM, Guardium, Optim, and Data Explorer. They will also learn about the integration between IBM Business Process Manager Express and IBM InfoSphere in terms of integrating information governance, big data, and business process management.

Foreword
Foreword
Big Data Integration and Governance with IBM InfoSphere
An Introduction to Big Data Governance
The Big Data Governance Framework
Big Data Types
Information Governance Disciplines
Industry and Functional Scenarios for Big Data Governance
The IBM Big Data Platform
IBM Big Data Products
IBM Big Data Platform Differentiators
Big Data Integration
Bulk Data Movement
Data Replication
Data Virtualization
Metadata
Establish a Glossary That Represents the Business Definitions for Key Big Data Terms
Tag Sensitive Big Data Within the Business Glossary
Maintain Technical Metadata to Support Data Lineage and Impact Analysis
Gather Metadata from Unstructured Documents to Support Enterprise Search
Big Data Security and Privacy
Identify Sensitive Big Data
Flag Sensitive Big Data Within the Metadata Repository
Mask Sensitive Big Data in Production and Non-Production Environments
Monitor Access to Sensitive Big Data by Privileged Users
Big Data Quality
Leverage Semi-Structured and Unstructured Data to Improve the Quality of Sparsely Populated Structured Data
Use Streaming Analytics to Address Data Quality Issues In-Memory Without Landing Interim Results to Disk
Cleanse Big Data Before or After Processing in Hadoop
Master Data Integration
Improve the Quality of Master Data to Support Big Data Analytics
Leverage Big Data to Improve the Quality of Master Data
Improve the Quality and Consistency of Key Reference Data to Support the Big Data Governance Program
Extract Meaning from Unstructured Text to Enrich Master Data
Enrich Customer Master Data with Insights from Social Media to Create Social MDM
Turbo-Charge MDM with Hadoop Technologies
Managing the Lifecycle of Big Data
Expand the Retention Schedule to Include Big Data Based on Local Regulations and Business Needs
Document Legal Holds and Support eDiscovery Requests
Compress and Archive Big Data on Hadoop to Reduce Storage Costs
Archive Big Data in Immutable Format with Seamless Access to Hadoop for Analytics
Manage the Lifecycle of Real-Time, Streaming Data
Defensibly Dispose of Big Data No Longer Required Based on Regulations and Business Needs
Process Data Governance with IBM InfoSphere
An Introduction to Process Data Governance
Retail Case Study: Process Data Governance of Social Media
Oil and Gas Case Study: Process Data Governance of Sensor Data
Healthcare Case Study: Process Data Governance of Big Claims Transaction Data
A Primer on Claim Codes Used by Health Plans
Notes
Appendix: Reviewer and Contributor Profiles

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