Powerbi Master

DAX (Data Analysis Expressions) mastery for Power BI semantic models. PROACTIVELY activate for: (1) writing DAX measures or calculated columns, (2) CALCULATE, FILTER, ALL, REMOVEFILTERS context-modification functions, (3) understanding filter context vs row context vs context transition, (4) time intelligence (SAMEPERIODLASTYEAR, DATEADD, YTD/MTD, TOTALYTD, DATESBETWEEN), (5) iterators (SUMX, AVERAGEX, FILTER), (6) variables (VAR/RETURN) and DAX optimization, (7) calculation groups, field parameters, and visual calculations, (8) WINDOW/INDEX/OFFSET/ORDERBY/PARTITIONBY/MATCHBY (window functions), (9) DAX user-defined functions (UDF), (10) DAX patterns for ratios, running totals, ranking. Provides: measure templates, time-intelligence patterns, optimization techniques (variables, FILTER vs CALCULATETABLE), context-transition explainers, and reference for window functions and calculation groups.

Core Power BI data modeling, source connectivity, and platform fundamentals. PROACTIVELY activate for: (1) Power BI data modeling and star-schema design, (2) relationships (active/inactive, bidirectional, USERELATIONSHIP), (3) data-source selection (DirectQuery vs Import vs Direct Lake vs composite), (4) incremental refresh setup, (5) gateway configuration (on-prem and VNet gateways), (6) streaming datasets and push-data scenarios, (7) Dataflow Gen2 basics, (8) Power BI common gotchas and pitfalls (bidirectional filtering, AutoExist, blank-row), (9) workspace identity and OAuth2 / service-principal auth, (10) semantic model architecture review. Provides: star-schema templates, mode-selection matrix, incremental refresh recipe, gateway setup steps, and a common-gotchas reference.

TMDL (Tabular Model Definition Language) mastery for Power BI semantic models. PROACTIVELY activate for: (1) writing or editing TMDL files, (2) TMDL syntax (model.tmdl, database.tmdl, relationships.tmdl, table folders), (3) TMDL serialization (TmdlSerializer, folder-based vs single-file), (4) TMDL view in Power BI Desktop, (5) TMDL vs TMSL vs BIM format selection, (6) TMDL expressions, calculation groups, perspectives, cultures, translations, annotations, (7) TMDL roles and security, (8) TMDL ref keyword and createOrReplace scripts, (9) TMDL CI/CD integration (Git, deployment), (10) TMDL hierarchies and partitions. Provides: TMDL syntax reference, folder-layout templates, serialization patterns, ref/createOrReplace recipes, and Git integration setup.

Power Query M language for ETL, transformations, and connector authoring. PROACTIVELY activate for: (1) writing Power Query M code, (2) query folding and Native Query verification, (3) data transformations (merge, append, pivot, unpivot, split column), (4) custom connector development, (5) Power Query parameters and dynamic source patterns, (6) performance optimization (folding, query reduction, partition strategy), (7) Table.TransformColumns, List.Generate, Record.Field functions, (8) error handling in M (try/otherwise, error records), (9) mashup engine internals, (10) ETL pipelines from folder/SharePoint/database sources. Provides: M language reference, query-folding diagnosis, transformation recipes, dynamic source patterns, error-handling templates, and performance tuning techniques.

Power BI deployment, CI/CD, governance, and administration. PROACTIVELY activate for: (1) Power BI deployment pipelines (Service deployment pipelines, fabric-cicd, custom workflows), (2) CI/CD for Power BI via GitHub Actions or Azure DevOps, (3) workspace management and roles, (4) row-level security (RLS) and object-level security (OLS), (5) capacity management (Premium, PPU, Fabric SKUs F2-F2048), (6) tenant settings and governance, (7) Power BI Report Server deployments, (8) service principal setup for automation, (9) data-gateway management. Provides: deployment-pipeline templates, GitHub Actions and Azure DevOps YAML, RLS/OLS implementation patterns, capacity sizing guidance, and service-principal auth recipes.

Microsoft Fabric integration with Power BI semantic models. PROACTIVELY activate for: (1) Microsoft Fabric platform tasks, (2) Direct Lake mode and OneLake connectivity, (3) Fabric lakehouse, warehouse, KQL Database, Eventstream, Data Activator, (4) Dataflow Gen2 ETL, (5) Fabric notebooks (PySpark, Spark SQL, semantic-link), (6) Fabric workspace and capacity (F-SKU) management, (7) delta tables and V-Order optimization, (8) medallion architecture (bronze/silver/gold), (9) Semantic Link / sempy / semantic-link-labs Python workflows, (10) Direct Lake fallback rules and mixed mode. Provides: Direct Lake setup, Fabric capacity sizing, lakehouse-to-semantic-model patterns, sempy/semantic-link-labs recipes, and end-to-end medallion architecture templates.

TMDL and PBIR validation, linting, and pre-deployment testing. PROACTIVELY activate for: (1) validating TMDL syntax before deploy, (2) validating PBIR schema, (3) catching TmdlFormatException / TmdlSerializationException early, (4) Best Practice Analyzer (BPA) rules and BPA CLI, (5) Tabular Editor BPA scripting, (6) PBI-Inspector / PBI-InspectorV2 / Fab Inspector, (7) PBIR JSON schema validation, (8) pre-deployment validation in CI, (9) fabric-cicd parameter.yml validation, (10) catching breaking changes between TMDL versions. Provides: BPA rule library, validation CLI commands, CI integration for validation, error catalog (TmdlFormatException, etc.), and a pre-deploy validation playbook.

Power BI REST API and Fabric REST API automation. PROACTIVELY activate for: (1) calling Power BI REST APIs, (2) embed-token generation (App Owns Data, User Owns Data), (3) service-principal authentication for Power BI, (4) dataset refresh API and refresh status polling, (5) push datasets and streaming, (6) Admin API (workspace/dataset enumeration), (7) Power BI Embedded and the JavaScript SDK (powerbi-client), (8) export-to-file API (PDF/PPTX/PNG), (9) Power BI automation via PowerShell (MicrosoftPowerBIMgmt), (10) Scanner API for tenant inventory, (11) app registration in Microsoft Entra ID. Provides: REST endpoint reference, OAuth/MSAL token recipes, embed-token patterns, refresh automation scripts, JavaScript SDK examples, and PowerShell module recipes.

Power BI performance optimization for slow reports, models, and queries. PROACTIVELY activate for: (1) report is slow or visuals take forever to load, (2) DAX Studio and VertiPaq Analyzer profiling, (3) Performance Analyzer in Power BI Desktop, (4) optimizing slow DAX measures, (5) slow visuals diagnosis, (6) aggregations and composite-model tuning, (7) query reduction techniques (visual settings, top N), (8) model size reduction (cardinality, calculated columns, summary tables), (9) VertiPaq compression tuning, (10) Direct Lake performance and fallback rules, (11) large-dataset (10GB+) optimization. Provides: profiling workflow with DAX Studio, VertiPaq compression checklist, aggregation-table patterns, model-size reduction techniques, and end-to-end performance investigation playbook.

Programmatic Power BI development with PBIR, PBIP, TMDL, TOM, and fabric-cicd. PROACTIVELY activate for: (1) creating Power BI reports programmatically (PBIR enhanced report format), (2) PBIR vs PBIR-Legacy selection (2026 default), (3) PBIP developer mode and Power BI project files, (4) Tabular Object Model (TOM) / .NET SDK scripting, (5) Tabular Editor scripting (C# scripts, advanced scripting), (6) pbi-tools workflows, (7) fabric-cicd Python deployments (FabricWorkspace, publish_all_items), (8) Fabric CLI (fab deploy), (9) Semantic Link / sempy / semantic-link-labs, (10) generating PBIX programmatically, (11) parameter.yml for environment-specific deployments, (12) ALM Toolkit. Provides: PBIR/PBIP project templates, fabric-cicd deploy.py, Tabular Editor scripting recipes, parameter.yml patterns, and end-to-end programmatic workflows.