Practical Data Migration, 3rd Edition

Table of contents

1. Front Cover
2. Half-Title Page
3. BCS, THE CHARTERED INSTITUTE FOR IT
4. Title Page
5. Copyright Page
6. Dedication
7. Contents
8. List of figures and tables
9. Author
10. Acknowledgements
11. Abbreviations
12. Glossary
13. Introduction
    1. What is the purpose of this book and who should read it?
    2. What type of data migration is covered?
    3. What is not covered in this book?
    4. The executive reader
    5. The practitioner
    6. What is new to version three of Practical Data Migration?
    7. Paragraph styles
14. Section 1: Principles and Overview
    1. 1. Data Migration: What’s All the fuss?
       1. What is data migration?
       2. Waterfall vs Agile
    2. 2. Golden Rules and Super Smart Tasks
       1. Golden Rules – the underlying principles in the book
       2. Super SMART Tasks and the mid-change cycle slump
    3. 3. PDMV3 Overview
       1. Agile and Waterfall
       2. Introducing the model
       3. Introducing technology
       4. PDMv3 provides all the answers
    4. 4. Migration Strategy and Governance
       1. Starting out on the right foot
       2. PDMv3 data migration strategy
       3. Control flows and project reporting
       4. Data migration strategy checklist
       5. Agile
       6. Getting the Data Migration Strategy Implemented
15. Section 2: Details
    1. 5. DQR
       1. Introducing data quality rules (DQR)
       2. DQR definition
       3. Waterfall vs Agile
       4. How are DQRs created?
       5. Long-running DQRs
       6. Software support
       7. Role of the DMZ
    2. 6. Demilitarised Zones and Protecting Commercial Interests
       1. The demilitarised zone (DMZ)
       2. Definition of the DMZ
       3. The impact of the DMZ
       4. Conclusion
    3. 7. Metadata and Key Business data area Decomposition
       1. Metadata and PDMv
       2. Project decomposition and key business data areas
    4. 8. Key data Stakeholder Management
       1. Introduction to key data stakeholders
       2. Key data stakeholder management and landscape analysis
    5. 9. Business Transformation Realisation
       1. Waterfall vs Agile
       2. Why business transformation realisation?
    6. 10. Landscape Analysis
       1. Waterfall vs Agile
       2. What is landscape analysis and why do we do it?
       3. Legacy data stores
       4. Profiling, data gaps and master data management
    7. 11. Gap Analysis and Mapping
       1. Waterfall vs Agile
       2. Gap analysis
       3. Data quality monitoring as a service
       4. Data mapping
       5. Data mapping is data migration?
       6. Data mapping, Agile vs Waterfall
       7. Inputs and outputs for data mapping
    8. 12. Migration Design and Execution
       1. Migration end-to-end design
       2. Extract, transform and load design
       3. Technical design
       4. Outputs of ETL design
       5. Decommissioning design
       6. Migration build, test and execute
    9. 13. Data Migration Testing
       1. Role of the DQR process
       2. DQRs – practical reasons
       3. Triage and root cause analysis
       4. Types of data migration testing
    10. 14. Legacy Decommissioning
        1. Waterfall vs Agile
        2. Executing the decommissioning design
    11. 15. Agile, Waterfall and Blended
        1. Three approaches to enterprise application migration
    12. 16. Release and Configuration Management
        1. Why releases?
16. Section 3: Rescuing Failing data Migration Projects
    1. 17. Rescuing Failing Data Migration Projects
       1. Recovery starts here
       2. Phases of recovery
17. Appendices
    1. A1 Configurable Items
    2. A2 Impact Analysis Frame
    3. A3 Data Migration Strategy Checklist
    4. A4 DQR Data Fields
    5. A5 Data Mapping
       1. Impact of technology
18. Index
19. Back Cover