Universal Meta Data Models

Create world-class MME solutions using thus set of ready-made meta data models.

Your company's prosperity depends on how well you gather, retain, and disseminate knowledge. By implementing a Managed Meta Data Environment (MME), you can effectively manage your data and information technology applications in order to achieve a strategic advantage over the competition. As a follow-up to Building and Managing the Meta Data Repository (Wiley), this book provides you with the tools to implement a world-class MME and create a systematic enterprise solution for meta data management. The authors first present an overview of the architectural components of the MME and include case studies that demonstrate how corporations are taking advantage of MME solutions in the real world.

They then dive into the details of the models that compose the MME and their major areas of interaction.

You'll find a complete set of meta data models that you can adapt to meet the needs of your company while saving countless hours of development time. Marco and Jennings offer an introduction to each model's definition, guidance on implementation, an example of reports that can be generated, and much more. With all of this information, you'll be able to model a meta data repository for:

• Enterprise systems
• XML, messaging, and business transactions
• IT portfolio management
• Business rules, business meta data, and data stewardship
• Complete universal meta model

• Introduction
• Part One: Presenting the Managed Meta Data Environment
• Chapter 1: Overview of the Managed Meta Data Environment
• Evolution of the Managed Meta Data Environment
• Typical Managed Meta Data Environment Objectives
• Increase Revenue and/or Decrease Costs
• Promote Public Health
• Adhere to Regulations
• Improve National Security
• Provide Education
• Ensure Public Safety
• Facing Corporate Challenges with an MME
• Provide IT Portfolio Management
• Reduce IT Redundancy
• Redundant Applications, Processes, and Data
• Needless IT Rework
• Redundant Hardware and Software
• Prevent IT Applications Failure
• Reduce IT Expenditures
• Enable Knowledge Management
• Adhere to Regulatory Requirements
• Enable Enterprise Applications
• Summary
• Chapter 2: The Managed Meta Data Environment Architecture
• MME Overview
• Meta Data Sourcing Layer
• Software Tools
• End Users
• Documents and Spreadsheets
• Messaging and Transactions
• Applications
• Web Sites and E-Commerce
• Third Parties
• Meta Data Integration Layer
• Meta Data Repository
• Meta Data Management Layer
• Archiving
• Backup
• Database Modifications
• Database Tuning
• Environment Management
• Job Scheduling
• Maintenance of Load Statistics
• Purging
• Maintaining of Query Statistics
• Query and Report Generation
• Recovery
• Security Processes
• Source Mapping and Movement
• User Interface Management
• Versioning
• Meta Data Marts
• Meta Data Delivery Layer
• Applications
• Data Warehouse and Data Marts
• End Users
• Messaging and Transactions
• Meta Data Marts
• Software Tools
• Third Parties
• Web Sites and E-Commerce
• MME Data Stewardship
• Understanding Data Stewardship
• Types of Data Stewards
• Executive Sponsor
• Chief Steward
• Business Steward
• Technical Steward
• Preparing for Data Stewardship
• Form a Charter
• Define and Prioritize Committee Activities
• Create Committee Rules of Order
• Establish Roles for Committee Members
• Design Standard Documents and Forms
• Data Stewardship Activities
• Define Data Domain Values
• Establish Data Quality Rules, Validate Them, and Resolve Them
• Set Up Business Rules and Security Requirements
• Create Business Meta Data Definitions
• Create Technical Meta Data Definitions
• Capability Maturity Model and the MME
• What Is the Capability Maturity Model?
• Why Is the SE-CMM Valuable?
• Purpose of the SE-CMM
• SE-CMM Levels
• Level 0: Not Performed
• Level 1: Performed Informally
• Level 2: Planned and Tracked
• Level 3: Well-Defined
• Level 4: Qualitatively Controlled
• Level 5: Continuously Improving
• Applying SE-CMM to Data Warehousing
• Level 0: Not Performed
• Level 1: Performed Informally
• Level 2: Planned and Tracked
• Level 3: Well-Defined
• Level 4: Qualitatively Controlled
• Level 5: Continuously Improving
• MME and the Common Warehouse Metamodel
• CWM Solution for Interchange Requirements
• CWM Technology and Approach
• Layered Architecture
• Supporting Technology
• The Future of the CWM
• Summary
• Chapter 3: Managed Meta Data Environment Applications
• MME Applications Examples
• Banking and Finance Industry Example
• Application Scenario
• Healthcare Insurance Industry Example
• Application Scenario
• Manufacturing Industry Example
• Application Scenario
• National Defense Organization Industry Example
• Application Scenario
• Pharmaceutical Industry Example
• Application Scenario
• Retail Industry Example
• Application Scenario
• Telecommunications Industry Example
• Application Scenario
• Case Studies: Two World-Class MME Initiatives
• Allstate
• Company Background
• Challenges and opportunities
• MME Solution Overview
• Data Stewardship
• MME Meta Data Sourcing Layer
• MME Meta Data Delivery Layer
• Allstate's Future MME Directions
• MME Challenges
• MME ROI
• RBC Financial Group
• Company Background
• Challenges and opportunities
• MME Solution Overview
• MME Meta Data Sourcing Layer
• MME Meta Data Delivery Layer
• MME Challenges
• MME ROI
• Summary
• Part Two: Universal Meta Data Models for the Meta Data Repository Environment
• Chapter 4: Universal Meta Data Model for Enterprise Systems
• Purpose of the Enterpriser Systems Meta Model
• Enterprise Systems Model Assumptions
• Enterprise Systems Subject Areas
• Data Package
• Data Relationships to Structure
• Data Movement and Transformations
• Expression Transformation
• Transformation Operational History
• Data Profiling
• Reports from the Enterprise Systems Meta Model
• Data Definition by System by Environment Report
• Data Structure Hierarchy Report
• System Data Quality Assessment Report
• Data Profiling Exceptions Report
• Data Impact Analysis Report
• Data Lineage Analysis Report
• Summary
• Chapter 5: Universal Meta Model for XML, Messaging, and Business Transactions
• Purpose of the XML Meta Models
• Model Assumptions
• Introduction to XML
• XML Schema Examples
• XML Categories
• Data-Centric XML: Data Structure vs. Process
• XML Standards
• XML, Messaging, and Business Transactions Subject Areas
• XML Schemas and DTDs
• XML Schema Structure
• DTD Structure
• XSLT: XML Transformation Language (XSLT)
•  Business Transactions
• Classification Scheme
• Reports from the XML, Messaging, and Business Transactionss Meta Model
• Business Transctions Meta Model
• XML Use Report: XML Top-Level Elements
• XML Use Report: Schema Imports
• XML Use Report: XML Process Send
• XML Use Report: XML Process Impact
• Process XML: Order Flow Views
• Summary
• Chapter 6: Universal Meta Model for IT Portfolio Management
• Purpose of the IT Portfolio Management Meta Model
• Assumptions in the IT Portfolio Management Meta Model
• IT Portfolio Management Subject Areas
• Service Management
• Software Management
• Hardware and Network Management
• Project Portfolio Management
• Data Quality Management
• Reports from the IT Portfolio Management Meta Model
• Software Module CRUD Report
• Hardware Obsolescent Report
• Data Storage Capacity Report
• Installed Software Patch Report
• Annual Vendor Software Fee Liability Report
• System Trouble Report Volume Report
• Unscheduled Maintenance by Component Report
• IT Project Resource Projection Report
• Project Success Rate Analysis Report
• Data Quality Exception Summary Report
• Summary
• Chapter 7: Universal Meta Model for Business Rules, Business Meta Data, and Data Stewardship
• Purpose of the Business Rules, Business Meta Data, and Data Stewardship Meta Model
• Assumptions in the Business Rules, Business Meta Data, and Data Stewardship Models
• Business Rules, Business Meta Data, and Data Stewardship Subject Areas
• Business Rules
• Business Meta Data
• Data Stewardship
• Reports from the Business Rules, Business Meta Data, and Data Stewardship Meta Models
• All Business Rules Report
• Business Rules by Business Rule Category Report
• Data Warehouse Customer Business Rules
• Data Groups by Subject Area
• Open and Pending Business Rule Issues
• Person by Organization and Manager
• Summary
• Chapter 8: The Complete Universal Meta Model
• A Complete High-Level Meta Model
• Implementation Considerations
• Levels of Data Models
• Database Unique IDs
• Code Tables
• Translating LDM to PDM
• Many-to-many Relationships
• Entity Subtyping
• Meta-Level Information Loss
• Multiple Inheritance
• Design Issues Revisited
• Data Quality Meta Data Mart
• OLAP Implementation of the Meta Data Mart
• Summary
• Conclusions
• Appendix A: Model Diagrams
• Appendix B: What’s on the CD-ROM?
• System Requirements
• Using the CD with Windows
• What's on the CD
• Author-created Materials
• Applications
• Troubleshooting
• Appendix C: Glossary
• Appendix D: Recommended Reading

I looked forward to a book that explained and poked into the concept of Meta data (a very hot topics in certain circles). Instead, I find incoherent explanations, references to COBOL, etc.

Well, I probably had too many assumptions on the quality of a book that sports two self-proclaimed gurus in the subject.

Forget about the book, you won't miss much.