Cover image for The DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK)

The DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK)

Author DAMA International
Release Date: 2009/04/01
ISBN: 9781935504009
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Book Description

Written by over 120 data management practitioners, the DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK) is the most impressive compilation of data management principals and best practices, ever assembled. It provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure. The equivalent of the PMBOK or the BABOK, the DAMA-DMBOK provides information on:

  • Data Governance
  • Data Architecture Management
  • Data Development
  • Database Operations Management
  • Data Security Management
  • Reference & Master Data Management
  • Data Warehousing & Business Intelligence Management
  • Document & Content Management
  • Meta Data Management
  • Data Quality Management
  • Professional Development

As an authoritative introduction to data management, the goals of the DAMA-DMBOK Guide are:

  • To build consensus for a generally applicable view of data management functions.
  • To provide standard definitions for commonly used data management functions, deliverables, roles, and other terminology.
  • To document guiding principles for data management.
  • To present a vendor-neutral overview to commonly accepted good practices, widely adopted methods and techniques, and significant alternative approaches.
  • To clarify the scope and boundaries of data management.
  • To act as a reference which guides readers to additional resources for further understanding.

The Editors are Mark Mosley, Editor - Development, Michael Brackett, Editor - Production, Susan Early, Assistant Editor, and Deborah Henderson, Project Sponsor. The Foreword is by John Zachman (DAMA I Lifetime Achievement Award recipient), the Preface is by John Schley (DAMA International President) and Deborah Henderson (DAMA Foundation President, DAMA International VP Education and Research), and the Afterword is by Michael Brackett (DAMA International Lifetime Achievement Award recipient).

From the Foreword by John Zachman:

The book is an exhaustive compilation of every possible subject and issue that warrants consideration in initiating and operating a Data Management responsibility in a modern Enterprise. It is impressive in its comprehensiveness. It not only identifies the goals and objectives of every Data Management issue and responsibility but it also suggests the natural organizational participants and end results that should be expected.

The publication began as a non-trivial, sorely needed compilation of articles and substantive facts about the little understood subject of data management orchestrated by some folks from the DAMA Chicago Chapter. It was unique at the time as there was little substantive reference material on the subject. It has grown to become this pragmatic practitioners handbook that deserves a place on every Data Management professionals bookshelf. There is a wealth of information for the novice data beginner, but it is also invaluable to the old timer as a check-list and validation of their understanding and responsibilities to ensure that nothing falls through the cracks! It is impressive in it breadth and completeness.

The DAMA-DMBOK Guide deserves a place on every Data Management professionals bookshelf and for the General Manager, it will serve as a guide for setting expectations and assigning responsibilities for managing and practicing what has become the very most critical resource owned by an Enterprise as it (the Enterprise) progresses into the Information Age: DATA!

Table of Contents

  1. Figures
  2. Tables
  3. Foreword
  4. Preface
  5. Acknowledgements
  6. 1 Introduction
    1. 1.1 Data: An Enterprise Asset
    2. 1.2 Data, Information, Knowledge
    3. 1.3 The Data Lifecycle
    4. 1.4 The Data Management Function
    5. 1.5 A Shared Responsibility
    6. 1.6 A Broad Scope
    7. 1.7 An Emerging Profession
    8. 1.8 A Growing Body of Knowledge
    9. 1.9 DAMA–The Data Management Association
    10. 1.10 Purpose of the DAMA-DMBOK Guide
    11. 1.11 Goals of the DAMA-DMBOK Guide
    12. 1.12 Audiences of the DAMA-DMBOK Guide
    13. 1.13 Using the DAMA-DMBOK Guide
    14. 1.14 Other BOK Guides
    15. 1.15 The DAMA Dictionary of Data Management
    16. 1.16 The DAMA-DMBOK Functional Framework
    17. 1.17 Structure of the DAMA-DMBOK Guide
    18. 1.18 Recurring Themes
  7. 2 Data Management Overview
    1. 2.1 Introduction
    2. 2.2 Mission and Goals
    3. 2.3 Guiding Principles
    4. 2.4 Functions and Activities
      1. 2.4.1 Data Management Activities
      2. 2.4.2 Activity Groups
    5. 2.5 Context Diagram Overview
      1. 2.5.1 Suppliers
      2. 2.5.2 Inputs
      3. 2.5.3 Participants
      4. 2.5.4 Tools
      5. 2.5.5 Primary Deliverables
      6. 2.5.6 Consumers
      7. 2.5.7 Metrics
    6. 2.6 Roles
      1. 2.6.1 Types of Organizations
      2. 2.6.2 Types of Individual Roles
    7. 2.7 Technology
      1. 2.7.1 Software Product Classes
      2. 2.7.2 Specialized Hardware
    8. 2.8 Recommended Reading
  8. 3 Data Governance
    1. 3.1 Introduction
    2. 3.2 Concepts and Activities
      1. 3.2.1 Data Governance
      2. 3.2.2 Data Stewardship
      3. 3.2.3 Data Governance and Stewardship Organizations
      4. 3.2.4 Data Management Services Organizations
      5. 3.2.5 The Data Management Executive
      6. 3.2.6 The Data Governance Office
    3. 3.3 Data Governance Activities
      1. 3.3.1 Data Strategy
      2. 3.3.2 Data Policies
      3. 3.3.3 Data Architecture
      4. 3.3.4 Data Standards and Procedures
      5. 3.3.5 Regulatory Compliance
      6. 3.3.6 Issue Management
      7. 3.3.7 Data Management Projects
      8. 3.3.8 Data Management Services
      9. 3.3.9 Data Asset Valuation
      10. 3.3.10 Communication and Promotion
      11. 3.3.11 Related Governance Frameworks
    4. 3.4 Summary
      1. 3.4.1 Guiding Principles
      2. 3.4.2 Process Summary
      3. 3.4.3 Organizational and Cultural Issues
    5. 3.5 Recommended Reading
      1. 3.5.1 Websites
      2. 3.5.2 Prominent Books
      3. 3.5.3 Regulatory and Compliance Books
      4. 3.5.4 General Books
  9. 4 Data Architecture Management
    1. 4.1 Introduction
    2. 4.2 Concepts and Activities
      1. 4.2.1 Architecture Overview
      2. 4.2.2 Activities
    3. 4.3 Summary
      1. 4.3.1 Guiding Principles
      2. 4.3.2 Process Summary
      3. 4.3.3 Organizational and Cultural Issues
    4. 4.4 Recommended Reading
      1. 4.4.1 Books
      2. 4.4.2 Articles and Websites
  10. 5 Data Development
    1. 5.1 Introduction
    2. 5.2 Concepts and Activities
      1. 5.2.1 System Development Lifecycle (SDLC)
      2. 5.2.2 Styles of Data Modeling
      3. 5.2.3 Data Modeling, Analysis, and Solution Design
      4. 5.2.4 Detailed Data Design
      5. 5.2.5 Data Model and Design Quality Management
      6. 5.2.6 Data Implementation
    3. 5.3 Summary
      1. 5.3.1 Guiding Principles
      2. 5.3.2 Data Development Process Summary
      3. 5.3.3 Organizational and Cultural Issues
    4. 5.4 Recommended Reading
      1. 5.4.1 Data Modeling and Database Design
      2. 5.4.2 Business Rules
      3. 5.4.3 Information Engineering
      4. 5.4.4 Agile Development
      5. 5.4.5 Object Orientation and Object-Oriented Design
      6. 5.4.6 Service-oriented architecture (SOA)
      7. 5.4.7 SQL
      8. 5.4.8 Software Process Improvement
      9. 5.4.9 XML
  11. 6 Data Operations Management
    1. 6.1 Introduction
    2. 6.2 Concepts and Activities
      1. 6.2.1 Database Support
      2. 6.2.2 Data Technology Management
    3. 6.3 Summary
      1. 6.3.1 Guiding Principles
      2. 6.3.2 Process Summary
      3. 6.3.3 Organizational and Cultural Issues
    4. 6.4 Recommended Reading
  12. 7 Data Security Management
    1. 7.1 Introduction
    2. 7.2 Concepts and Activities
      1. 7.2.1 Understand Data Security Needs and Regulatory Requirements
      2. 7.2.2 Define Data Security Policy
      3. 7.2.3 Define Data Security Standards
      4. 7.2.4 Define Data Security Controls and Procedures
      5. 7.2.5 Manage Users, Passwords, and Group Membership
      6. 7.2.6 Manage Data Access Views and Permissions
      7. 7.2.7 Monitor User Authentication and Access Behavior
      8. 7.2.8 Classify Information Confidentially
      9. 7.2.9 Audit Data Security
    3. 7.3 Data Security in an Outsourced World
    4. 7.4 Summary
      1. 7.4.1 Guiding Principles
      2. 7.4.2 Process Summary
      3. 7.4.3 Organizational and Cultural Issues
    5. 7.5 Recommended Reading
      1. 7.5.1 Texts and Articles
      2. 7.5.2 Major Privacy and Security Regulations
  13. 8 Reference and Master Data Management
    1. 8.1 Introduction
    2. 8.2 Concepts and Activities
      1. 8.2.1 Reference Data
      2. 8.2.2 Master Data
      3. 8.2.3 Understand Reference and Master Data Integration Needs
      4. 8.2.4 Identify Reference and Master Data Sources and Contributors
      5. 8.2.5 Define and Maintain the Data integration Architecture
      6. 8.2.6 Implement Reference and Master Data Management Solutions
      7. 8.2.7 Define and Maintain Match Rules
      8. 8.2.8 Establish Golden Records
      9. 8.2.9 Define and Maintain Hierarchies and Affiliations
      10. 8.2.10 Plan and Implement Integration of New Data Sources
      11. 8.2.11 Replicate and Distribute Reference and Master Data
      12. 8.2.12 Manage Changes to Reference and Master Data
    3. 8.3 Summary
      1. 8.3.1 Guiding Principles
      2. 8.3.2 Process Summary
      3. 8.3.3 Organizational and Cultural Considerations
    4. 8.4 Recommended Reading
  14. 9 Data Warehousing and Business Intelligence Management
    1. 9.1 Introduction
    2. 9.2 Concepts and Activities
      1. 9.2.1 Data Warehousing—A Brief Retrospective and Historical Tour
      2. 9.2.2 DW / BI Architecture and Components
      3. 9.2.3 Tactical, Strategic and Operational BI
      4. 9.2.4 Types of Data Warehousing
      5. 9.2.5 Dimensional Data Modeling Concepts and Terminology
    3. 9.3 DW-BIM Activities
      1. 9.3.1 Understand Business Intelligence Information Needs
      2. 9.3.2 Define and Maintain the DW-BI Architecture
      3. 9.3.3 Implement Data Warehouses and Data Marts
      4. 9.3.4 Implement Business Intelligence Tools and User Interfaces
      5. 9.3.5 Process Data for Business Intelligence
      6. 9.3.6 Monitor and Tune Data Warehousing Processes
      7. 9.3.7 Monitor and Tune BI Activity and Performance
    4. 9.4 Summary
      1. 9.4.1 Guiding Principles
      2. 9.4.2 Process Summary
      3. 9.4.3 Organizational and Cultural Issues
    5. 9.5 Recommended Reading
      1. 9.5.1 Data Warehousing
      2. 9.5.2 Business Intelligence
      3. 9.5.3 Data Mining
      4. 9.5.4 OLAP
  15. 10 Document and Content Management
    1. 10.1 Introduction
    2. 10.2 Concepts and Activities
      1. 10.2.1 Unstructured Data
      2. 10.2.2 Document / Record Management
      3. 10.2.3 Content Management
    3. 10.3 Summary
      1. 10.3.1 Guiding Principles
      2. 10.3.2 Process Summary
      3. 10.3.3 Organizational and Cultural Issues
    4. 10.4 Recommended Reading
      1. 10.4.1 Document / Content Management
      2. 10.4.2 Records Management
      3. 10.4.3 Enterprise Information Portals
      4. 10.4.4 Meta-data in Library Science
      5. 10.4.5 Semantics in XML Documents
      6. 10.4.6 Unstructured Data and Business Intelligence
      7. 10.4.7 Standards
      8. 10.4.8 E-Discovery
  16. 11 Meta-data Management
    1. 11.1 Introduction
    2. 11.2 Concepts and Activities
      1. 11.2.1 Meta-data Definition
      2. 11.2.2 Meta-data History 1990 - 2008
      3. 11.2.3 Meta-data Strategy
      4. 11.2.4 Meta-data Management Activities
    3. 11.3 Summary
      1. 11.3.1 Guiding Principles
      2. 11.3.2 Process Summary
      3. 11.3.3 Organizational and Cultural Issues
    4. 11.4 Recommended Reading
      1. 11.4.1 General Reading
      2. 11.4.2 Meta-data in Library Science
      3. 11.4.3 Geospatial Meta-data Standards
      4. 11.4.4 ISO Meta-data Standards
  17. 12 Data Quality Management
    1. 12.1 Introduction
    2. 12.2 Concepts and Activities
      1. 12.2.1 Data Quality Management Approach
      2. 12.2.2 Develop and Promote Data Quality Awareness
      3. 12.2.3 Define Data Quality Requirements
      4. 12.2.4 Profile, Analyze and Assess Data Quality
      5. 12.2.5 Define Data Quality Metrics
      6. 12.2.6 Define Data Quality Business Rules
      7. 12.2.7 Test and Validate Data Quality Requirements
      8. 12.2.8 Set and Evaluate Data Quality Service Levels
      9. 12.2.9 Continuously Measure and Monitor Data Quality
      10. 12.2.10 Manage Data Quality Issues
      11. 12.2.11 Clean and Correct Data Quality Defects
      12. 12.2.12 Design and Implement Operational DQM Procedures
      13. 12.2.13 Monitor Operational DQM Procedures and Performance
    3. 12.3 Data Quality Tools
      1. 12.3.1 Data Profiling
      2. 12.3.2 Parsing and Standardization
      3. 12.3.3 Data Transformation
      4. 12.3.4 Identity Resolution and Matching
      5. 12.3.5 Enhancement
      6. 12.3.6 Reporting
    4. 12.4 Summary
      1. 12.4.1 Setting Data Quality Guiding Principles
      2. 12.4.2 Process Summary
      3. 12.4.3 Organizational and Cultural Issues
    5. 12.5 Recommended Reading
  18. 13 Professional Development
    1. 13.1 Characteristics of a Profession
    2. 13.2 DAMA Membership
    3. 13.3 Continuing Education and Training
    4. 13.4 Certification
      1. 13.4.1 How Do You Obtain a CDMP?
      2. 13.4.2 CDMP Examination Criteria
      3. 13.4.4 CDMP Qualifying Examinations
      4. 13.4.5 Accepted Vendor Training Certifications
      5. 13.4.6 Preparation for Taking Exams
      6. 13.4.7 Taking CDMP Exams
      7. 13.4.8 Professional Development / Recertification
    5. 13.5 Professional Ethics
    6. 13.6 Notable Data Management Professionals
      1. 13.6.1 Lifetime Achievement Award
      2. 13.6.2 Professional Achievement Award
      3. 13.6.3 Government Achievement Award
      4. 13.6.4 Academic Achievement Award
      5. 13.6.5 DAMA Community Award
  19. Afterword
  20. A1 Data Management Suppliers
  21. A2 Data Management Inputs
  22. A3 Data Management Participants
  23. A4 Data Management Tools
  24. A5 Data Management Primary Deliverables
  25. A6 Data Management Consumers
  26. A7 Data Management Metrics
  27. A8 Software Product Classes
  28. A9 Summary Process Tables
    1. A9.1 Data Governance
    2. A9.2 Data Architecture Management
    3. A9.3 Data Development
    4. A9.4 Data Operations Management
    5. A9.5 Data Security Management
    6. A9.6 Reference and Master Data Management
    7. A9.7 Data Warehouse and Business Intelligence Management
    8. A9.8 Document and Content Management
    9. A9.9 Meta-data Management
    10. A9.10 Data Quality Management
  29. A10 Standards
    1. A10.1 Non-United States Privacy Laws:
    2. A10.2 United States Privacy Laws:
    3. A10.3 Industry-Specific Security and Privacy Regulations:
    4. A10.4 Standards
  30. Bibliography
  31. Index