InsightfulAnalytics DAX Optimisation
Skills and references for writing, debugging, and optimizing DAX in semantic models.
Optimization
For systematic DAX query performance optimization, read the workflow reference first:
references/dax-performance-optimization.md — Tiered framework (4 tiers), phased workflow, decision guide, and error handling.
Detailed reference files (progressive disclosure — consult as directed by the workflow):
references/engine-internals.md— FE/SE architecture, xmSQL, compression/segments, SE fusion, trace diagnosticsreferences/dax-patterns.md— Tier 1 DAX patterns (DAX001–DAX021) + Tier 2 query structure (QRY001–QRY004)references/model-optimization.md— Tier 3 model patterns (MDL001–MDL009) + Tier 4 Direct Lake (DL001–DL002)
Trace capture and performance profiling:
- Local models (Power BI Desktop): Use the Tabular Editor CLI
te query(see thete-cliskill) first; as an alternative, theconnect-pbidskill covers FE/SE timing (performance-profiling.md) and intermediate result inspection (evaluateandlog-debugging.md). - Remote models (Fabric Service / XMLA): Run DAX with the Tabular Editor CLI
te query(-s <workspace> -d <model>) against the workspace XMLA endpoint; see thete-cliskill (tabular-editor plugin). - Power BI Modeling MCP: also available for trace and query if you prefer an MCP tool; reach for it after the options above.
Every capture route above times the DAX query. None of them evaluate a dynamic format string, which a rendered visual pays once per cell, so a visual can cost materially more than the query the harness measures. See references/dax-performance-optimization.md, Trace Capture Methods.
Related Skills
dax-standard— Authoring measures in the house style; the default for any new measure (this skill is for tuning existing ones)semantic-model— Model design, build, and auditing including DAX anti-patterns and best practicesconnect-pbid(pbi-desktop plugin) — Trace capture, performance profiling, EVALUATEANDLOG debugginglineage-analysis— Impact analysis before model changes