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IBM InfoSphere : a Platform for Big Data Governance and Process Data Governance.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Ketchum :
M C Press,
2013.
|
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- ""Cover""; ""Copyright""; ""Dedication""; ""About the Author""; ""Contents""; ""Foreword by David Corrigan""; ""Foreword by Inderpal Bhandari""; ""PART I: Big Data Integration and Governance with IBM InfoSphere""; ""Chapter 1: An Introduction to Big Data Governance""; ""Chapter 2: The Big Data Governance Framework""; ""2.1 Big Data Types""; ""2.2 Information Governance Disciplines""; ""2.3 Industry and Functional Scenarios for Big Data Governance""; ""Chapter 3: The IBM Big Data Platform""; ""3.1 IBM Big Data Products""; ""3.2 IBM Big Data Platform Differentiators""
- ""Chapter 4: Big Data Integration""""4.1 Bulk Data Movement""; ""4.2 Data Replication""; ""4.3 Data Virtualization""; ""Chapter 5: Metadata""; ""5.1 Establish a Glossary That Represents the Business Definitions for Key Big Data Terms""; ""5.2 Tag Sensitive Big Data Within the Business Glossary""; ""5.3 Maintain Technical Metadata to Support Data Lineage and Impact Analysis""; ""5.4 Gather Metadata from Unstructured Documents to Support Enterprise Search""; ""Chapter 6: Big Data Security and Privacy""; ""6.1 Identify Sensitive Big Data""
- ""6.2 Flag Sensitive Big Data Within the Metadata Repository""""6.3 Mask Sensitive Big Data in Production and Non-Production Environments""; ""6.4 Monitor Access to Sensitive Big Data by Privileged Users""; ""Chapter 7: Big Data Quality""; ""7.1 Leverage Semi-Structured and Unstructured Data to Improve the Quality of Sparsely Populated Structured Data""; ""7.2 Use Streaming Analytics to Address Data Quality Issues In-Memory Without Landing Interim Results to Disk""; ""7.3 Cleanse Big Data Before or After Processing in Hadoop""; ""Chapter 8: Master Data Integration""
- ""8.1 Improve the Quality of Master Data to Support Big Data Analytics""""8.2 Leverage Big Data to Improve the Quality of Master Data""; ""8.3 Improve the Quality and Consistency of Key Reference Data to Support the Big Data Governance Program""; ""8.4 Extract Meaning from Unstructured Text to Enrich Master Data""; ""8.5 Enrich Customer Master Data with Insights from Social Media to Create Social MDM""; ""8.6 Turbo-Charge MDM with Hadoop Technologies""; ""Chapter 9: Managing the Lifecycle of Big Data""
- ""9.1 Expand the Retention Schedule to Include Big Data Based on Local Regulations and Business Needs""""9.2 Document Legal Holds and Support eDiscovery Requests""; ""9.3 Compress and Archive Big Data on Hadoop to Reduce Storage Costs""; ""9.4 Archive Big Data in Immutable Format with Seamless Access to Hadoop for Analytics""; ""9.5 Manage the Lifecycle of Real-Time, Streaming Data""; ""9.6 Defensibly Dispose of Big Data No Longer Required Based on Regulations and Business Needs""; ""PART II: Process Data Governance with IBM InfoSphere""