Data Technical Debt: Looking Beyond Code
summary
Data technical debt costs are concrete: bad data costs the US an estimated $3 trillion per year and the average organization loses about $15 million a year. Strategies include database refactoring (65+ refactorings available), a practical rename pattern using a first_name/fname trigger interim schema, and building automated regression test suites. Disciplined Agile offers choices for avoiding, accepting, or repaying data debt and governance, reuse and architecture changes reduce coupling that breaks hundreds of apps.
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chapters (16)
- 0:00Intro
- 0:47Scott Ambler
- 1:58What is Data Technical Debt?
- 3:43Why Does Data Technical Debt Occur?
- 14:47Technical Debt Quadrant
- 16:06Explore the initial Scope
- 19:36Build Quality In From the Beginning
- 20:55Identify the initial Technical Strategy
- 21:42Architecture Owner
- 22:59Be Enterprise Aware
- 24:57Enterprise Architecture Teams
- 26:25Following Organizational Guidelines
- 28:59Technical Debt Avoidance Strategies
- 31:11Database Refactoring
- 36:17Explicitly Accept Technical Debt
- 37:02Challenges
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