Technics Publications

Pragmatic Data Governance

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Pragmatic Data Governance, by William Carroll

Starting a new data governance program? Resetting a program that’s stalled? On a tight budget?  



Big Picture

DG-IBG – The Data Governance Integrated Business Glossary

WKRP – Wisdom and Knowledge Rescue Project

Business As Usual Versus Startup

Chapter Notes


Reasons For Data Governance

Data Governance – Strategy, Goal, Tactics, and Activities



Tactics = Objectives


All Together – Pragmatic Data Governance Method

Maturity Assessment – DMBOK and CMMI DMM



Self Assessment


Chapter Notes

Business as Usual

Objective – Identify Organizational Units and People

Subview – {Person and Business Unit}

Business As Usual Activities

Objective – Support DG Committees and Data Steward Participation

Subview – {Governing Body Management}

Business As Usual Activities

Objective – Identify and Prioritize Data Issues

Subview – {Data Issue Register}

Business As Usual Activities

Objective – Document Data Issues’ Metadata

Subview – {XREF – Business Attribute 360 – WKRP}

Subview – {XREF – Data Issue, Business Attribute, Application, and BI Object}

Subview – {Data Quality}

Subview – {RACI – Business Attributes, Entities, Subject Areas}

Subview – {RACI – Data Issue, Application, BI Object}

Subview – {Lineage}

Pre-Built Views

Business As Usual Activities

Objective – Checkpoint And Facilitate Data Issue Resolution


Consolidate Data Issues?

Stakeholder Consultations

Checkpoint – Missing Success Factors

Update DSWG and EDGE

Pre-Built Views

Business As Usual Activities

Objective – Report Progress

Quarterly Progress Report

Annual Satisfaction Survey

Pre-Built Views

Business As Usual Activities

Chapter Notes

Last Words


Appendix – Terms of Reference – DSWG

Appendix -FAQ – Frequently Asked Questions

Appendix – Views and Pre-Built Views

Views For All Tables

Pre-Built Views To Support Day-to-Day Activities

Appendix – DG-IBG Entity/Table Comments

Appendix – Abbreviations

Starting a new data governance program? Resetting a program that’s stalled? On a tight budget?

Apply the “what and how” to deliver data governance. Pragmatic Data Governance is an approach that was able to deliver a functioning program in less than two years. Implement Business-Led Data Governance is the strategy and Synchronize Organizational Opinion Regarding Shared Data Assets is the goal. Six supporting tactical objectives and their activities support the goal and deliver business-led data governance.

Pragmatic Data Governance distills on-the-job experience from assignments with banking and government clients over a 14-year period, enhanced with books, webinars, and training modules. Special mention goes to the insights gained from the DAMA Data Management Body of Knowledge (DMBOK).

A minimalist and hand-made metadata repository called the Data Governance Integrated Business Glossary (DG-IBG) supports the Pragmatic Data Governance approach. A data governance program catalogs and documents an organization’s data asset inventory with business and technical metadata, such as definitions, data quality rules, and table and column details. The DG-IBG is modeled using Oracle SQL Developer Data Modeler and implemented with 60+ tables and 320+ columns in Microsoft SQL Server Express, both free downloads from Oracle and Microsoft.

By capturing and documenting data issues in the DG-IBG, we can support business-side stakeholders in prioritizing and resolving data issues. Reflecting on the data issues gives us insight into data management success factors that may be absent, such as formal data quality or master data management programs. This insight supports cost/benefit analysis in business cases for these initiatives.

The author has provided these free downloads to accompany the book:

About William

William Carroll is a data management practitioner and DAMA Certified Data Management Professional (CDMP) at the Master level. He has leadership, mentoring, and hands-on experience with 10 of 11 DAMA knowledge areas, for 20+ organizations, in seven different industry verticals, in four countries and on two continents. He has started data governance, data quality, and metadata management practices at two international banks, worked on 14 DW/BI projects, prepared designs for three MDM initiatives, worked as a data architect in multiple organizations, has DBA experience with four database products, written programs in six languages on four OS platforms, worked in a data center at the beginning of his career, and started writing programs in high school. In sharing Pragmatic Data Governance, he’s following the concept that “Happiness comes when your work and words are of benefit to others.”


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