Book description
What do you know about your data? And how do you know what you know about your data?
Information governance initiatives address corporate concerns about the quality and reliability of information in planning and decision-making processes. Metadata management refers to the tools, processes, and environment that are provided so that organizations can reliably and easily share, locate, and retrieve information from these systems.
Enterprise-wide information integration projects integrate data
from these systems to one location to generate required reports and
analysis.
During this type of implementation process, metadata management
must be provided along each step to ensure that the final reports
and analysis are from the right data sources, are complete, and
have quality.
This IBM® Redbooks® publication introduces the information governance initiative and highlights the immediate needs for metadata management. It explains how IBM InfoSphere™ Information Server provides a single unified platform and a collection of product modules and components so that organizations can understand, cleanse, transform, and deliver trustworthy and context-rich information. It describes a typical implementation process. It explains how InfoSphere Information Server provides the functions that are required to implement such a solution and, more importantly, to achieve metadata management.
This book is for business leaders and IT architects with an overview of metadata management in information integration solution space. It also provides key technical details that IT professionals can use in a solution planning, design, and implementation process.
Table of contents
- Front cover
- Notices
- Preface
- Part 1 Overview and concepts
- Chapter 1. Information governance and metadata management
-
Chapter 2. Solution planning and metadata management
- 2.1 Getting started with solution planning
- 2.2 Stakeholders
- 2.3 Integrated solution data flow
-
2.4 Typical implementation process flow
- 2.4.1 Defining business requirements
- 2.4.2 Building business centric vocabulary
- 2.4.3 Developing data model
- 2.4.4 Documenting source data
- 2.4.5 Assessing and monitoring data quality
- 2.4.6 Building up the metadata repository
- 2.4.7 Transforming data
- 2.4.8 Developing BI solutions
- 2.4.9 Generating enterprise reports and lineage
- 2.5 Conclusion
-
Chapter 3. IBM InfoSphere Information Server approach
- 3.1 Overview of InfoSphere Information Server
- 3.2 Platform infrastructure
-
3.3 Product modules and components
- 3.3.1 InfoSphere Blueprint Director
- 3.3.2 InfoSphere DataStage and InfoSphere QualityStage
- 3.3.3 InfoSphere Information Analyzer
- 3.3.4 InfoSphere Discovery
- 3.3.5 InfoSphere FastTrack
- 3.3.6 InfoSphere Business Glossary
- 3.3.7 InfoSphere Metadata Workbench
- 3.3.8 InfoSphere Information Server Manager, ISTools and InfoSphere Metadata Asset Manager
- 3.3.9 InfoSphere Data Architect
- 3.3.10 Cognos Business Intelligence software
-
3.4 Solution development: Mapping product modules and components to solution processes
- 3.4.1 Defining the business requirements
- 3.4.2 Building business centric vocabulary
- 3.4.3 Developing data model
- 3.4.4 Documenting source data
- 3.4.5 Assessing and monitoring data quality
- 3.4.6 Building up the metadata repository
- 3.4.7 Transforming data
- 3.4.8 Developing BI solutions
- 3.4.9 Generating enterprise reports and lineage
- 3.5 Deployment architecture and topologies
- 3.6 Conclusion
- Part 2 Implementation
- Chapter 4. Use-case scenario
- Chapter 5. Implementation planning
-
Chapter 6. Building a business-centric vocabulary
- 6.1 Introduction to InfoSphere Business Glossary
- 6.2 Business glossary and information governance
- 6.3 Creating the business glossary content
- 6.4 Deploying a business glossary
- 6.5 Managing the term authoring process with a workflow
- 6.6 Searching and exploring with InfoSphere Business Glossary
- 6.7 Multiple ways of accessing InfoSphere Business Glossary
- 6.8 Conclusion
- Chapter 7. Source documentation
-
Chapter 8. Data relationship discovery
- 8.1 Introduction to InfoSphere Discovery
- 8.2 Creating a project
- 8.3 Performing column analysis
- 8.4 Identifying and classifying sensitive data
- 8.5 Assigning InfoSphere Business Glossary terms to physical assets
- 8.6 Reverse engineering a data model
- 8.7 Performing value overlap analysis
- 8.8 Discovering transformation logic
- 8.9 Conclusion
-
Chapter 9. Data quality assessment and monitoring
- 9.1 Introduction to IBM InfoSphere Information Analyzer
- 9.2 InfoSphere Information Analyzer data rules
- 9.3 Creating a rule
- 9.4 Data rule examples
- 9.5 Data rules and performance consideration
- 9.6 Rule sets
- 9.7 Metrics
- 9.8 Monitoring data quality
- 9.9 Using HTTP/CLI API
- 9.10 Managing rules
- 9.11 Deploying rules, rule sets, and metrics
- 9.12 Rule stage for InfoSphere DataStage
- 9.13 Conclusion
- Chapter 10. Building up the metadata repository
- Chapter 11. Data transformation
- Chapter 12. Enterprise reports and lineage generation
- Related publications
- Back cover
Product information
- Title: Metadata Management with IBM InfoSphere Information Server
- Author(s):
- Release date: October 2011
- Publisher(s): IBM Redbooks
- ISBN: 9780738435992
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