A Context Test Harness for Power BI Models

TL;DR

• Define representative queries and expected outcomes.
• Use them to detect context regressions.

The problem

• Context issues are hard to detect until users complain.
• Model changes can silently break answers.

Why it matters

• Tests provide early warning for instability.
• They enable safe iteration on the model.

Symptoms

• Unexpected changes in KPI values after model updates.
• AI answers that drift without data changes.

Root causes

• No regression tests for filter context.
• Model updates lack validation checks.

What good looks like

• A small set of representative queries with expected ranges.
• Regular test runs before deployment.

How to fix

• Define 10–20 representative questions.
• Capture expected outcomes or ranges.
• Run tests after every model change.

Pitfalls

• Testing too many edge cases and ignoring core KPIs.
• Using stale expected values.

Checklist

• Test harness defined and documented.
• Tests run on every release.
• Failures reviewed and resolved.

Framework placement

Primary ARF layer: Context Stability. Diagnostic bridge: data-movement-reliability, semantic-reliability, execution-reliability.