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Implement Security and Governance

MS LearnSecure data access in Microsoft FabricWorkspace roles: Admin, Member, Contributor, Viewer; item sharing›MS DocsPermission model in Microsoft FabricWorkspace roles, item permissions, sharing model overview›MS DocsSecurity overview in Microsoft FabricEnd-to-end security: workspace, item, data-level controls›

MS DocsShare Fabric itemsShare individual items without workspace role – restricted access patterns›MS LearnSecure a Microsoft Fabric data warehouseItem-level security in warehouse: row, column, and object security›

MS DocsRow-level security in OneLakeSQL predicate syntax, enforcement engines, RLS + CLS combination›MS DocsColumn-level security in OneLakeCLS: Spark, SQL endpoint, semantic model behavior›MS DocsObject-level security in FabricHide tables/columns from specific roles in semantic models›MS DocsOneLake security access control modelEffective role evaluation: UNION/INTERSECTION semantics›

MS LearnGovern data in Microsoft Fabric with PurviewPurview integration, sensitivity labels, data classification›MS DocsSensitivity labels in Microsoft FabricApply, propagate, and inherit sensitivity labels across items›

MS DocsEndorsement in Microsoft FabricPromoted vs Certified endorsement, who can certify, UI walkthrough›MS LearnAdminister and govern Microsoft Fabric (LP)4-module path covering endorsement, Purview, security, admin›

Maintain the Analytics Development Lifecycle

MS LearnImplement CI/CD in Microsoft FabricGit integration, version control, deployment pipelines – 8 units›MS DocsGet started with Git integrationConnect workspace to Azure DevOps or GitHub, branching strategy›

MS DocsPower BI Desktop projects overviewPBIP file format, source control-friendly project files›MS DocsPower BI project (PBIP) and Git integrationSave as project, commit to Git, CI/CD pipeline patterns›

MS LearnImplement CI/CD in Microsoft FabricModule unit 4: deployment pipelines – dev/test/prod stages›MS DocsGet started with deployment pipelinesStage creation, workspace assignment, deploy with rules›MS DocsChoose the best Fabric CI/CD workflow optionfabric-cicd Python lib, Bulk Import API, pipeline comparison›

MS DocsImpact analysis in Microsoft FabricDownstream dependency tracking for lakehouses, warehouses, dataflows›MS DocsData source view in the Fabric portalIdentify consumers of a dataset or dataflow›

MS DocsSemantic model connectivity with the XMLA endpointRead/write XMLA, Tabular Editor, ALM Toolkit, deployment patterns›MS DocsDeploy and manage semantic modelsDeployment automation via XMLA, REST APIs, and pipelines›

MS DocsPower BI template (.pbit) filesCreate templates, distribute pre-connected reports›MS DocsPower BI data source (.pbids) filesPBIDS connection shortcut files for report authors›MS DocsUse semantic models across workspacesShared / certified semantic models, live connection patterns›

Get Data

MS LearnImplement a Lakehouse with Microsoft Fabric (LP)7-module path: connections, pipelines, Delta, medallion architecture›MS DocsData source management in Microsoft FabricGateways, on-prem connectors, cloud connections›

MS DocsOneLake catalog in Microsoft FabricData discovery, endorsement filtering, domain browsing›MS DocsReal-Time hub in Microsoft FabricDiscover streaming data sources: Event Hubs, Eventstreams, KQL databases›

MS LearnIngest data with Microsoft Fabric (LP)6 modules: Dataflows Gen2, pipelines, Spark, RTI, Eventstreams›MS DocsDataflows Gen2 in Microsoft FabricPower Query-based ingestion, scheduled refresh, gateway options›

MS DocsDecide between a Lakehouse and a Warehouse in FabricSide-by-side decision matrix: SQL, Spark, unstructured data›MS LearnGet started with lakehouses in Microsoft FabricLakehouse architecture, when to use vs warehouse›MS LearnGet started with data warehouses in Microsoft FabricWarehouse concepts, T-SQL, loading, modeling basics›

MS DocsOne Logical Copy – OneLake availability in EventhouseEnable OneLake availability for KQL database tables›MS DocsOneLake integration with semantic modelsExpose semantic model data in OneLake via Delta format›

Transform Data

MS DocsViews in Fabric Data WarehouseCreate and manage views for abstraction and security›MS DocsStored procedures in Fabric Data WarehouseT-SQL stored procedures: create, execute, parameterize›MS DocsUser-defined functions in Fabric WarehouseScalar and table-valued functions in T-SQL›

MS LearnUse Apache Spark in Microsoft FabricPySpark: add columns, derived features, Delta writes›MS LearnOrganize a Fabric lakehouse using medallion architectureSilver → Gold enrichment patterns, conformed dimensions›

MS DocsDimensional modeling overview in Fabric WarehouseFact tables, dimension tables, surrogate keys, SCD types›MS DocsDimensional modeling: load process for dimension and fact tablesETL orchestration: staging → dimensions → facts → logging›MS DocsStar schema guidance for Power BIWhy star schema: query performance, DAX simplicity, usability›

MS LearnUse Apache Spark in Microsoft FabricPySpark: groupBy, agg, join, union, window functions›MS DocsT-SQL in Microsoft Fabric WarehouseSQL editor, aggregations, joins, CTAS, MERGE patterns›

MS LearnUse Apache Spark in Microsoft FabricPySpark: dropDuplicates(), fillna(), handling nulls and late data›MS DocsData quality best practices in FabricNull handling, duplicate detection, type coercion in pipelines›

MS DocsData types in Fabric Data WarehouseSupported T-SQL types, implicit/explicit conversions, best practices›MS LearnWork with Delta Lake tables in Microsoft FabricSchema enforcement, schema evolution, CAST in Delta›

Query and Analyze Data

MS DocsVisual Query Editor in Fabric WarehouseNo-code query building: filter, join, aggregate, preview›MS LearnGet started with data warehouses in Microsoft FabricModule covers Visual Query Editor as a transformation tool›

MS LearnWork with Delta Lake tables in Microsoft FabricDelta SQL: SELECT, MERGE, time travel, aggregate patterns›MS DocsPerformance guidelines in Fabric Data WarehouseFilter early, avoid SELECT *, distributed plan hints›

MS LearnWork with real-time data in a Microsoft Fabric eventhouseKQL: summarize, bin(), join, project, extend, parse›MS DocsKQL language referenceFull KQL reference: operators, functions, syntax›MS DocsKQL query optimization best practicesFilter early, materialize(), avoid repeated subexpressions›

MS LearnModel data in Power BI (LP)DAX fundamentals: measures, calculated columns, context transition›MS DocsDAX referenceFull DAX function reference: aggregation, text, date, filter, iterator functions›MS DocsDAX best practicesCALCULATE, FILTER, iterators, SUMX vs SUM, context transition›

Design and Build Semantic Models

MS DocsStorage modes in Power BI DesktopImport vs DirectQuery vs Direct Lake vs Dual mode decision matrix›MS DocsDirect Lake mode overviewDirect Lake: zero-copy from OneLake, fallback behavior, limitations›

MS DocsStar schema guidance for Power BIWhy star schema: query performance, DAX simplicity, usability›MS DocsUnderstand relationships in semantic modelsRelationship types: single, many-to-many, active vs inactive›

MS DocsMany-to-many relationships in Power BIBridge tables, weak relationships, bi-directional filtering pitfalls›MS DocsRelationship guidance in Power BIActive vs inactive, role-playing dimensions, relationship selection›

MS LearnModel data in Power BI (LP)DAX: iterators (SUMX, COUNTX), table filtering (CALCULATE, FILTER)›MS DocsDAX windowing functionsINDEX, OFFSET, WINDOW functions for row-by-row calculations›MS DocsDAX information functionsISBLANK, ISNUMBER, ISERROR, USERPRINCIPALNAME, USERNAME›

MS DocsCalculation groups in Analysis Services / Power BIDefine calculation groups via Tabular Editor: time intelligence, currency›MS DocsDynamic format strings for measuresConditional formatting in measures with FORMAT() and calculation groups›MS DocsField parameters in Power BILet users switch between fields/measures dynamically in reports›

MS DocsLarge semantic model storage formatPremium/Fabric large models: ABFS storage, dataset size limits›MS DocsComposite models in Power BIDirectQuery + Import hybrid, DirectQuery to Power BI datasets›

Optimize Enterprise-Scale Semantic Models

MS DocsOptimization guide for Power BIModel design, DAX patterns, aggregations, visual query reduction›MS DocsQuery reduction options in Power BICross-filter reduction, Apply button, slicer optimization›MS DocsPerformance Analyzer in Power BI DesktopMeasure DAX query time, visual render time, and other processing time›

MS DocsDAX variables best practicesVAR…RETURN pattern: avoid recalculation, improve readability›MS DocsAvoid using FILTER as a table argumentUse KEEPFILTERS, column comparisons instead of row-by-row FILTER›MS DocsAppropriate use of error functions in DAXIFERROR, ISERROR performance cost and alternatives›

MS DocsDirect Lake mode overview and fallback behaviorWhen Direct Lake falls back to DirectQuery: framing, limits›MS DocsDirect Lake dataset refresh and framingFraming operations, scheduled refresh, semantic model refresh›

MS DocsDirect Lake on OneLake vs SQL analytics endpointWhen to use each: performance, fallback mode, metadata handling›MS DocsSQL analytics endpoint performanceSQL endpoint query execution, framing, and metadata refresh›

MS DocsIncremental refresh for semantic modelsDefine date range, configure refresh policy, hybrid tables›MS DocsConfigure incremental refresh and real-time dataRangeStart/RangeEnd parameters, publish, manage partitions›

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