A Practical Triage Order for Slow Power BI Reports
When a report feels slow, teams often jump straight to visuals or DAX. In practice, the fastest route is to isolate where the time is really going, then fix the highest-leverage layer first.
Insights
Notes from BI engineering.
Practical writing on performance, semantic models, report quality, and the work between a business question and a reliable answer.
8 published articles · Power BI and analytics engineering
Start here · Testing and report quality
A Pattern Catalog for Automated Measure Testing in Power BI
Most Power BI teams don't automate measure testing, but not because they don't want to. They don't because nobody has written down what the patterns actually are. This is the catalog I'd hand a new BI engineer on day one.
7 min read
Read articlePower BI performance
Performance guidance focused on isolating the real bottleneck before effort gets wasted in the wrong layer.
Semantic model governance
Governance guidance centered on change visibility, semantic-model discipline, and safer release decisions.
When to Redesign a Semantic Model vs. Patch It
Not every semantic-model problem needs a rebuild. The right call depends on how deep the structural issues go, how much trust the current model still carries, and whether a patch leaves behind something you would want to hand off. A decision matrix, a worked example, and the failure modes that catch teams out.
Semantic Model Governance Before Change: What to Check First
Governance becomes real just before a change is deployed. A lightweight pre-change checklist catches most avoidable semantic-model risk before it reaches users.
PBIP/PBIR workflow
Workflow notes on making report and model changes easier to inspect, review, and deploy with confidence.
A PBIP and PBIR Workflow That Makes Report Reviews Safer
PBIP and PBIR are most useful when they reduce ambiguity in report change review. The value is not the file format itself; it is the clearer workflow it enables.
Analytics engineering
Practical notes on delivery handoffs, analytics engineering discipline, and reducing ambiguity before it reaches BI.
Analytics Engineering Handoffs That Make Reporting Easier to Trust
Reporting quality improves when upstream handoffs are clearer. A few basic analytics-engineering practices reduce ambiguity before the BI layer has to compensate for it.
Testing and report quality
Quality checks and publishing habits that tighten validation and reduce avoidable report regressions.
A Pattern Catalog for Automated Measure Testing in Power BI
Most Power BI teams don't automate measure testing, but not because they don't want to. They don't because nobody has written down what the patterns actually are. This is the catalog I'd hand a new BI engineer on day one.
Five Signs Your Power BI Report Needs a Structural Review
Some report problems are not about wrong numbers or slow visuals. They are structural: the report was built in a way that makes maintenance, trust, and usability harder over time.
Report Quality Checks to Run Before Publishing
Many report issues are not data problems. They are publishing problems that should have been caught in a short QA pass before the report reached users.
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