Review Microsoft Fabric analytics engineering artifacts — Fabric Data Warehouse T-SQL design and anti-patterns, dimensional modeling (star schema, fact and dimension tables, relationships), semantic model design (Direct Lake vs Import vs DirectQuery selection, table layout, relationship cardinality), DAX measure correctness and optimization (iterators, filter context, variables, CALCULATE), data preparation and transformation quality, and reusable certified semantic models feeding Power BI reports. Use to fix bad star schemas, slow DAX, untrustworthy measures, and warehouse anti-patterns. Distinct from governance: this is build quality and modeling correctness, not RLS or workspace trust. Static review only; production warehouse schema changes and semantic-model deployment are escalated.
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryData & analyticsStars0
About this skill
Review Microsoft Fabric analytics engineering artifacts — Fabric Data Warehouse T-SQL design and anti-patterns, dimensional modeling (star schema, fact and dimension tables, relationships), semantic model design (Direct Lake vs Import vs DirectQuery selection, table layout, relationship cardinality), DAX measure correctness and optimization (iterators, filter context, variables, CALCULATE), data preparation and transformation quality, and reusable certified semantic models feeding Power BI reports. Use to fix bad star schemas, slow DAX, untrustworthy measures, and warehouse anti-patterns. Distinct from governance: this is build quality and modeling correctness, not RLS or workspace trust. Static review only; production warehouse schema changes and semantic-model deployment are escalated.
Quick start
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Review Microsoft Fabric analytics engineering artifacts — Fabric Data Warehouse T-SQL design and anti-patterns, dimensional modeling (star schema, fact and dimension tables, relationships), semantic model design (Direct Lake vs Import vs DirectQuery selection, table layout, relationship cardinality), DAX measure correctness and optimization (iterators, filter context, variables, CALCULATE), data preparation and transformation quality, and reusable certified semantic models feeding Power BI reports. Use to fix bad star schemas, slow DAX, untrustworthy measures, and warehouse anti-patterns. Distinct from governance: this is build quality and modeling correctness, not RLS or workspace trust. Static review only; production warehouse schema changes and semantic-model deployment are escalated.
About this listing
Category
Data & analytics
Reported license
Apache-2.0
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI