Data Warehouse Build Issue Log
This is a practical guide to building a issue log for a data warehouse build project — a register of problems that have occurred and need resolving, adapted to the realities of building a central data warehouse for analytics.
What a Issue Log is
A issue log is a register of problems that have occurred and need resolving. For the full concept and how it works in general, see Issue Log. On a data warehouse build project it plays the same role, tuned to this kind of work.
Why it matters for a Data Warehouse Build project
Data Warehouse Build projects live or die on building a central data warehouse for analytics. A well-built issue log gives the team a shared, explicit reference for exactly that — reducing ambiguity, aligning stakeholders, and making problems visible early enough to act. Skipping it, or doing it generically, is how data warehouse build projects drift into avoidable delay and cost.
What to include
- Issue description
- Priority and severity
- Owner
- Resolution and status
Data Warehouse Build-specific considerations
Tailor the issue log to the risks that most often derail data warehouse build projects:
- Source-system integration
- Data modelling decisions
- Governance and access control
Example
On a real data warehouse build project, the issue log would be shaped by building a central data warehouse for analytics. In particular, it should explicitly account for the project’s biggest risks — source-system integration, data modelling decisions, governance and access control — rather than treating them as afterthoughts.