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DAMA - Data Management Book of Knowledge 2 DMBOK2 [full book - second edition 2017]

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  • Data Science
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  • Vrije Universiteit Amsterdam (VU)
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  • DAMA-DMBOK

DAMA International is pleased to release the second edition of the DAMA Guide to the Data Management Book of Knowledge (DMBOK2). A data management framework for data driven organizations.

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  • March 29, 2018
  • 628
  • 2017/2018
  • Manual
  • Unknown

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  • dama
  • dmbok
  • dmbok2
  • second edition
  • data framework
  • framework
  • governance

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Order 13965 by Steven Bauer on March 13, 2018

, DAMA-DMBOK
DATA MANAGEMENT BODY OF KNOWLEDGE
SECOND EDITION




DAMA International




Technics Publications
BASKING RIDGE, NEW JERSEY




Order 13965 by Steven Bauer on March 13, 2018

, Dedicated to the memory of
Patricia Cupoli, MLS, MBA, CCP, CDMP
(May 25, 1948 – July 28, 2015)

for her lifelong commitment to the Data Management profession
and her contributions to this publication.



Published by:




2 Lindsley Road
Basking Ridge, NJ 07920 USA

https://www.TechnicsPub.com

Senior Editor: Deborah Henderson, CDMP
Editor: Susan Earley, CDMP
Production Editor: Laura Sebastian-Coleman, CDMP, IQCP
Bibliography Researcher: Elena Sykora, DGSP
Collaboration Tool Manager: Eva Smith, CDMP

Cover design by Lorena Molinari

All rights reserved. No part of this book may be reproduced or transmitted in any form or by any means, electronic
or mechanical, including photocopying, recording or by any information storage and retrieval system, without
written permission from the publisher, except for the inclusion of brief quotations in a review.

The author and publisher have taken care in the preparation of this book, but make no expressed or implied
warranty of any kind and assume no responsibility for errors or omissions. No liability is assumed for incidental or
consequential damages in connection with or arising out of the use of the information or programs contained herein.

All trade and product names are trademarks, registered trademarks or service marks of their respective companies
and are the property of their respective holders and should be treated as such.

Second Edition

First Printing 2017

Copyright © 2017 DAMA International

ISBN, Print ed. 9781634622349
ISBN, PDF ed. 9781634622363
ISBN, Server ed. 9781634622486
ISBN, Enterprise ed. 9781634622479

Library of Congress Control Number: 2017941854




Order 13965 by Steven Bauer on March 13, 2018

,Order 13965 by Steven Bauer on March 13, 2018

, Contents

Preface _________________________________________________________ 15
Chapter 1: Data Management _______________________________________ 17
1. Introduction ____________________________________________________________ 17
2. Essential Concepts _______________________________________________________ 18
2.1 Data ______________________________________________________________________ 18
2.2 Data and Information ________________________________________________________ 20
2.3 Data as an Organizational Asset _______________________________________________ 20
2.4 Data Management Principles __________________________________________________ 21
2.5 Data Management Challenges _________________________________________________ 23
2.6 Data Management Strategy ___________________________________________________ 31
3. Data Management Frameworks ____________________________________________ 33
3.1 Strategic Alignment Model____________________________________________________ 33
3.2 The Amsterdam Information Model ____________________________________________ 34
3.3 The DAMA-DMBOK Framework _______________________________________________ 35
3.4 DMBOK Pyramid (Aiken) _____________________________________________________ 39
3.5 DAMA Data Management Framework Evolved ___________________________________ 40
4. DAMA and the DMBOK ___________________________________________________ 43
5. Works Cited / Recommended ______________________________________________ 46

Chapter 2: Data Handling Ethics ____________________________________ 49
1. Introduction ____________________________________________________________ 49
2. Business Drivers ________________________________________________________ 51
3. Essential Concepts _______________________________________________________ 52
3.1 Ethical Principles for Data ____________________________________________________ 52
3.2 Principles Behind Data Privacy Law ____________________________________________ 53
3.3 Online Data in an Ethical Context ______________________________________________ 56
3.4 Risks of Unethical Data Handling Practices ______________________________________ 56
3.5 Establishing an Ethical Data Culture ____________________________________________ 60
3.6 Data Ethics and Governance __________________________________________________ 64
4. Works Cited / Recommended ______________________________________________ 65

Chapter 3: Data Governance ________________________________________ 67
1. Introduction ____________________________________________________________ 67
1.1 Business Drivers ____________________________________________________________ 70
1.2 Goals and Principles _________________________________________________________ 71
1.3 Essential Concepts __________________________________________________________ 72
2. Activities _______________________________________________________________ 79
2.1 Define Data Governance for the Organization ____________________________________ 79
2.2 Perform Readiness Assessment _______________________________________________ 79
2.3 Perform Discovery and Business Alignment _____________________________________ 80
2.4 Develop Organizational Touch Points___________________________________________ 81
2.5 Develop Data Governance Strategy _____________________________________________ 82
2.6 Define the DG Operating Framework ___________________________________________ 82
2.7 Develop Goals, Principles, and Policies __________________________________________ 83
2.8 Underwrite Data Management Projects _________________________________________ 84
2.9 Engage Change Management __________________________________________________ 85

1


Order 13965 by Steven Bauer on March 13, 2018

,2 • DMBOK2



2.10 Engage in Issue Management ________________________________________________ 86
2.11 Assess Regulatory Compliance Requirements___________________________________ 87
2.12 Implement Data Governance _________________________________________________ 88
2.13 Sponsor Data Standards and Procedures _______________________________________ 88
2.14 Develop a Business Glossary _________________________________________________ 90
2.15 Coordinate with Architecture Groups _________________________________________ 90
2.16 Sponsor Data Asset Valuation ________________________________________________ 91
2.17 Embed Data Governance ____________________________________________________ 91
3. Tools and Techniques____________________________________________________ 92
3.1 Online Presence / Websites___________________________________________________ 92
3.2 Business Glossary ___________________________________________________________ 92
3.3 Workflow Tools ____________________________________________________________ 93
3.4 Document Management Tools_________________________________________________ 93
3.5 Data Governance Scorecards __________________________________________________ 93
4. Implementation Guidelines _______________________________________________ 93
4.1 Organization and Culture_____________________________________________________ 93
4.2 Adjustment and Communication ______________________________________________ 94
5. Metrics ________________________________________________________________ 94
6. Works Cited / Recommended _____________________________________________ 95

Chapter 4: Data Architecture _______________________________________ 97
1. Introduction ___________________________________________________________ 97
1.1 Business Drivers ____________________________________________________________ 99
1.2 Data Architecture Outcomes and Practices _____________________________________ 100
1.3 Essential Concepts _________________________________________________________ 101
2. Activities _____________________________________________________________ 109
2.1 Establish Data Architecture Practice __________________________________________ 110
2.2 Integrate with Enterprise Architecture ________________________________________ 115
3. Tools ________________________________________________________________ 115
3.1 Data Modeling Tools________________________________________________________ 115
3.2 Asset Management Software _________________________________________________ 115
3.3 Graphical Design Applications _______________________________________________ 115
4. Techniques ___________________________________________________________ 116
4.1 Lifecycle Projections _______________________________________________________ 116
4.2 Diagramming Clarity _______________________________________________________ 116
5. Implementation Guidelines ______________________________________________ 117
5.1 Readiness Assessment / Risk Assessment ______________________________________ 118
5.2 Organization and Cultural Change ____________________________________________ 119
6. Data Architecture Governance ___________________________________________ 119
6.1 Metrics ___________________________________________________________________ 120
7. Works Cited / Recommended ____________________________________________ 120

Chapter 5: Data Modeling and Design _______________________________ 123
1. Introduction __________________________________________________________ 123
1.1 Business Drivers ___________________________________________________________ 125
1.2 Goals and Principles ________________________________________________________ 125
1.3 Essential Concepts _________________________________________________________ 126
2. Activities _____________________________________________________________ 152
2.1 Plan for Data Modeling______________________________________________________ 152




Order 13965 by Steven Bauer on March 13, 2018

, CONTENTS • 3



2.2 Build the Data Model _______________________________________________________ 153
2.3 Review the Data Models _____________________________________________________ 158
2.4 Maintain the Data Models ___________________________________________________ 159
3. Tools _________________________________________________________________ 159
3.1 Data Modeling Tools ________________________________________________________ 159
3.2 Lineage Tools _____________________________________________________________ 159
3.3 Data Profiling Tools ________________________________________________________ 160
3.4 Metadata Repositories ______________________________________________________ 160
3.5 Data Model Patterns ________________________________________________________ 160
3.6 Industry Data Models _______________________________________________________ 160
4. Best Practices __________________________________________________________ 161
4.1 Best Practices in Naming Conventions _________________________________________ 161
4.2 Best Practices in Database Design _____________________________________________ 161
5. Data Model Governance _________________________________________________ 162
5.1 Data Model and Design Quality Management ___________________________________ 162
5.2 Data Modeling Metrics ______________________________________________________ 164
6. Works Cited / Recommended _____________________________________________ 166

Chapter 6: Data Storage and Operations _____________________________ 169
1. Introduction ___________________________________________________________ 169
1.1 Business Drivers ___________________________________________________________ 171
1.2 Goals and Principles ________________________________________________________ 171
1.3 Essential Concepts _________________________________________________________ 172
2. Activities ______________________________________________________________ 193
2.1 Manage Database Technology ________________________________________________ 194
2.2 Manage Databases _________________________________________________________ 196
3. Tools _________________________________________________________________ 209
3.1 Data Modeling Tools ________________________________________________________ 209
3.2 Database Monitoring Tools __________________________________________________ 209
3.3 Database Management Tools _________________________________________________ 209
3.4 Developer Support Tools ____________________________________________________ 209
4. Techniques ____________________________________________________________ 210
4.1 Test in Lower Environments _________________________________________________ 210
4.2 Physical Naming Standards __________________________________________________ 210
4.3 Script Usage for All Changes _________________________________________________ 210
5. Implementation Guidelines_______________________________________________ 210
5.1 Readiness Assessment / Risk Assessment ______________________________________ 210
5.2 Organization and Cultural Change ____________________________________________ 211
6. Data Storage and Operations Governance ___________________________________ 212
6.1 Metrics ___________________________________________________________________ 212
6.2 Information Asset Tracking __________________________________________________ 213
6.3 Data Audits and Data Validation ______________________________________________ 213
7. Works Cited / Recommended _____________________________________________ 214

Chapter 7: Data Security __________________________________________ 217
1. Introduction ___________________________________________________________ 217
1.1 Business Drivers ___________________________________________________________ 220
1.2 Goals and Principles ________________________________________________________ 222
1.3 Essential Concepts _________________________________________________________ 223




Order 13965 by Steven Bauer on March 13, 2018

,4 • DMBOK2



2. Activities _____________________________________________________________ 245
2.1 Identify Data Security Requirements __________________________________________ 245
2.2 Define Data Security Policy __________________________________________________ 247
2.3 Define Data Security Standards_______________________________________________ 248
3. Tools ________________________________________________________________ 256
3.1 Anti-Virus Software / Security Software _______________________________________ 256
3.2 HTTPS ___________________________________________________________________ 256
3.3 Identity Management Technology ____________________________________________ 257
3.4 Intrusion Detection and Prevention Software ___________________________________ 257
3.5 Firewalls (Prevention) ______________________________________________________ 257
3.6 Metadata Tracking _________________________________________________________ 257
3.7 Data Masking/Encryption ___________________________________________________ 258
4. Techniques ___________________________________________________________ 258
4.1 CRUD Matrix Usage ________________________________________________________ 258
4.2 Immediate Security Patch Deployment ________________________________________ 258
4.3 Data Security Attributes in Metadata __________________________________________ 258
4.4 Metrics ___________________________________________________________________ 259
4.5 Security Needs in Project Requirements _______________________________________ 261
4.6 Efficient Search of Encrypted Data ____________________________________________ 262
4.7 Document Sanitization ______________________________________________________ 262
5. Implementation Guidelines ______________________________________________ 262
5.1 Readiness Assessment / Risk Assessment ______________________________________ 262
5.2 Organization and Cultural Change ____________________________________________ 263
5.3 Visibility into User Data Entitlement __________________________________________ 263
5.4 Data Security in an Outsourced World _________________________________________ 264
5.5 Data Security in Cloud Environments __________________________________________ 265
6. Data Security Governance _______________________________________________ 265
6.1 Data Security and Enterprise Architecture _____________________________________ 265
7. Works Cited / Recommended ____________________________________________ 266

Chapter 8: Data Integration and Interoperability______________________ 269
1. Introduction __________________________________________________________ 269
1.1 Business Drivers ___________________________________________________________ 270
1.2 Goals and Principles ________________________________________________________ 272
1.3 Essential Concepts _________________________________________________________ 273
2. Data Integration Activities _______________________________________________ 286
2.1 Plan and Analyze __________________________________________________________ 286
2.2 Design Data Integration Solutions ____________________________________________ 289
2.3 Develop Data Integration Solutions ___________________________________________ 291
2.4 Implement and Monitor _____________________________________________________ 293
3. Tools ________________________________________________________________ 294
3.1 Data Transformation Engine/ETL Tool ________________________________________ 294
3.2 Data Virtualization Server ___________________________________________________ 294
3.3 Enterprise Service Bus ______________________________________________________ 294
3.4 Business Rules Engine ______________________________________________________ 295
3.5 Data and Process Modeling Tools _____________________________________________ 295
3.6 Data Profiling Tool _________________________________________________________ 295
3.7 Metadata Repository _______________________________________________________ 296
4. Techniques ___________________________________________________________ 296




Order 13965 by Steven Bauer on March 13, 2018

, CONTENTS • 5



5. Implementation Guidelines_______________________________________________ 296
5.1 Readiness Assessment / Risk Assessment ______________________________________ 296
5.2 Organization and Cultural Change ____________________________________________ 297
6. DII Governance_________________________________________________________ 297
6.1 Data Sharing Agreements ___________________________________________________ 298
6.2 DII and Data Lineage _______________________________________________________ 298
6.3 Data Integration Metrics ____________________________________________________ 299
7. Works Cited / Recommended _____________________________________________ 299

Chapter 9: Document and Content Management_______________________ 303
1. Introduction ___________________________________________________________ 303
1.1 Business Drivers ___________________________________________________________ 305
1.2 Goals and Principles ________________________________________________________ 305
1.3 Essential Concepts _________________________________________________________ 307
2. Activities ______________________________________________________________ 323
2.1 Plan for Lifecycle Management _______________________________________________ 323
2.2 Manage the Lifecycle _______________________________________________________ 326
2.3 Publish and Deliver Content _________________________________________________ 329
3. Tools _________________________________________________________________ 330
3.1 Enterprise Content Management Systems ______________________________________ 330
3.2 Collaboration Tools ________________________________________________________ 333
3.3 Controlled Vocabulary and Metadata Tools _____________________________________ 333
3.4 Standard Markup and Exchange Formats ______________________________________ 333
3.5 E-discovery Technology _____________________________________________________ 336
4. Techniques ____________________________________________________________ 336
4.1 Litigation Response Playbook ________________________________________________ 336
4.2 Litigation Response Data Map ________________________________________________ 337
5. Implementation Guidelines_______________________________________________ 337
5.1 Readiness Assessment / Risk Assessment ______________________________________ 338
5.2 Organization and Cultural Change ____________________________________________ 339
6. Documents and Content Governance _______________________________________ 340
6.1 Information Governance Frameworks _________________________________________ 340
6.2 Proliferation of Information _________________________________________________ 342
6.3 Govern for Quality Content __________________________________________________ 342
6.4 Metrics ___________________________________________________________________ 343
7. Works Cited / Recommended _____________________________________________ 344

Chapter 10: Reference and Master Data _____________________________ 347
1. Introduction ___________________________________________________________ 347
1.1 Business Drivers ___________________________________________________________ 349
1.2 Goals and Principles ________________________________________________________ 349
1.3 Essential Concepts _________________________________________________________ 350
2. Activities ______________________________________________________________ 370
2.1 MDM Activities ____________________________________________________________ 371
2.2 Reference Data Activities ____________________________________________________ 373
3. Tools and Techniques ___________________________________________________ 375
4. Implementation Guidelines_______________________________________________ 375
4.1 Adhere to Master Data Architecture ___________________________________________ 376
4.2 Monitor Data Movement ____________________________________________________ 376




Order 13965 by Steven Bauer on March 13, 2018

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4.3 Manage Reference Data Change ______________________________________________ 376
4.4 Data Sharing Agreements ___________________________________________________ 377
5. Organization and Cultural Change ________________________________________ 378
6. Reference and Master Data Governance____________________________________ 378
6.1 Metrics ___________________________________________________________________ 379
7. Works Cited / Recommended ____________________________________________ 379

Chapter 11: Data Warehousing and Business Intelligence_______________ 381
1. Introduction __________________________________________________________ 381
1.1 Business Drivers ___________________________________________________________ 383
1.2 Goals and Principles ________________________________________________________ 383
1.3 Essential Concepts _________________________________________________________ 384
2. Activities _____________________________________________________________ 394
2.1 Understand Requirements __________________________________________________ 394
2.2 Define and Maintain the DW/BI Architecture ___________________________________ 395
2.3 Develop the Data Warehouse and Data Marts ___________________________________ 396
2.4 Populate the Data Warehouse ________________________________________________ 397
2.5 Implement the Business Intelligence Portfolio __________________________________ 398
2.6 Maintain Data Products _____________________________________________________ 399
3. Tools ________________________________________________________________ 402
3.1 Metadata Repository _______________________________________________________ 402
3.2 Data Integration Tools ______________________________________________________ 403
3.3 Business Intelligence Tools Types ____________________________________________ 403
4. Techniques ___________________________________________________________ 407
4.1 Prototypes to Drive Requirements ____________________________________________ 407
4.2 Self-Service BI _____________________________________________________________ 408
4.3 Audit Data that can be Queried _______________________________________________ 408
5. Implementation Guidelines ______________________________________________ 408
5.1 Readiness Assessment / Risk Assessment ______________________________________ 408
5.2 Release Roadmap __________________________________________________________ 409
5.3 Configuration Management __________________________________________________ 409
5.4 Organization and Cultural Change ____________________________________________ 410
6. DW/BI Governance_____________________________________________________ 411
6.1 Enabling Business Acceptance _______________________________________________ 411
6.2 Customer / User Satisfaction_________________________________________________ 412
6.3 Service Level Agreements ___________________________________________________ 412
6.4 Reporting Strategy _________________________________________________________ 412
6.5 Metrics ___________________________________________________________________ 413
7. Works Cited / Recommended ____________________________________________ 414

Chapter 12: Metadata Management ________________________________ 417
1. Introduction __________________________________________________________ 417
1.1 Business Drivers ___________________________________________________________ 420
1.2 Goals and Principles ________________________________________________________ 420
1.3 Essential Concepts _________________________________________________________ 421
2. Activities _____________________________________________________________ 434
2.1 Define Metadata Strategy____________________________________________________ 434
2.2 Understand Metadata Requirements __________________________________________ 435
2.3 Define Metadata Architecture ________________________________________________ 436




Order 13965 by Steven Bauer on March 13, 2018

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