Data Strategy: Uplift Data Governance While Retiring Tech Debt, by Krupesh Desai
Turn legacy system retirement into an opportunity to strengthen data governance and build lasting control over your organization’s information.
Part I: Why Governance Fails
Chapter 1: The Larger Picture, Revisited
Chapter 2: Governance Is a Capability, Not a State
Chapter 3: The Appetite
Chapter 4: The Governance Vacuum
Part II: Doing It
Chapter 5: Start With Discovery
Chapter 6: Roles That Survive
Chapter 7: The Conformance Chain
Chapter 8: Registers, Not Documents
Chapter 9: The Committee That Decides
Chapter 10: The Performance Side
Part III: Making It Travel
Chapter 11: Compliance as a By-Product
Chapter 12: Same Core, Different Laws
Chapter 13: Handing It Over
Chapter 14: The Question Set
The Last Question
Executives, data governance professionals, and technology leaders will learn how to use system replacement initiatives to establish accountable, sustainable data management practices.
Many organizations invest heavily in data migration while overlooking the governance weaknesses their projects expose. Unclear ownership, inconsistent definitions, undocumented decisions, and uncertain retention requirements create risks that persist long after implementation. Drawing on a real-world engagement involving sixteen core systems at an Australian municipal council, this book demonstrates how structured discovery can address these weaknesses while supporting migration planning. It builds on the method in the author’s earlier book, Data Migration Framework: Removing the Tech Debt.
Apply a practical data governance framework that connects legal obligations to specific data assets and defensible retention decisions. Find the business owners, data stewards, and IT custodians already doing the work, and make their roles formal. Establish actionable governance registers, decision-making committees, and audit trails that provide evidence of compliance. Evaluate what information should be migrated, archived, or lawfully destroyed, and document the reasoning behind each decision.
Move beyond regulatory compliance to improve data quality, master data management, and organizational performance. Align governance activities with business objectives, establish consistent definitions, and prioritize the information that matters most. Practical examples, reusable methods, and focused exercises show how to build capabilities that remain effective after consultants and project teams depart.
Build a governance capability your organization can operate, maintain, and trust. Put the methods in this book to work.
Krupesh Desai is a Certified Data Management Professional (CDMP) with more than fifteen years spent solving hard data problems across industries. He started as a software engineer in database recovery and replication, and grew through data migration, integration, governance, and enterprise data strategy. He spent more than a decade in New Zealand, where he led multiple legacy decommissioning and migration programs in the public health sector, delivering migration and analytics solutions with business continuity intact. He is now based in Melbourne, Australia.
He is the author of Data Migration Framework: Removing the Tech Debt (Technics Publications, 2025), a practical guide to moving legacy data from discovery to cutover while lifting governance maturity along the way. This second book comes from practicing what the first one preached, applying its method end to end in the field. That framework has since grown into Data View House, a governance platform he founded, where every piece of data carries the law that binds it at each stage of its life.
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