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
Part 1. Overview and concepts
Chapter 1. Information governance and metadata management
Chapter 2. Solution planning and metadata management
Chapter 3. IBM InfoSphere Information Server approach
Part 2. Implementation
Chapter 4. Use-case scenario
Chapter 5. Implementation planning
Chapter 6. Building a business-centric vocabulary
Chapter 7. Source documentation
Chapter 8. Data relationship discovery
Chapter 9. Data quality assessment and monitoring
Chapter 10. Building up the metadata repository
Chapter 11. Data transformation
Chapter 12. Enterprise reports and lineage generation
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