A polished executive report is the visible end of a much longer analytical process. The quality of the final Power BI page depends on decisions made far earlier: how requirements were framed, which sources were trusted, how fields were cleaned, how tables were modeled, how metrics were defined, and how exceptions were tested. Home/Microsoft/Microsoft PL-300: From Raw Data to an Executive Power BI ReportMicrosoftPublished October 3, 2026On this pageStart by defining the decision and audienceInventory sources and assign authorityProfile the data before building transformation logicClean and shape data where the…

Enterprise BI architecture has traditionally forced a familiar choice. Import models provide fast in-memory analytics but require data to be copied and refreshed into the semantic model. DirectQuery keeps data in the source and can expose fresher results, but report performance becomes more dependent on source latency, query translation, and concurrency. Home/Microsoft/Microsoft DP-600: Direct Lake Changes the Enterprise BI Trade-OffMicrosoftPublished October 3, 2026On this pageDirect Lake starts with OneLake and Delta tablesIt is not the same as querying files for every visualDirect Lake on OneLake and Direct Lake on SQL…

A semantic model can be perfectly correct on the day it launches and still fail six months later because the business changes around it. Products are reorganized, fiscal calendars move, customer hierarchies merge, metrics are redefined, security rules become more granular, and new fact tables arrive with different grains. Home/Microsoft/Microsoft DP-600: Semantic Models That Survive Business ChangeMicrosoftPublished October 3, 2026On this pageStart with business entities that are likely to persistDefine the grain of every fact before adding measuresUse conformed dimensions to isolate changeSeparate business measures from report-specific presentationHistory needs an…

A DAX measure can return the right number and still be a poor production measure. The difference appears when the model grows, more users arrive, the same calculation is reused across dozens of visuals, or a report page asks the engine to evaluate the expression repeatedly under different filter contexts. Home/Microsoft/Microsoft DP-600: DAX Performance Beyond Correct ResultsMicrosoftPublished October 3, 2026On this pageCorrect DAX can still do unnecessary workPerformance starts with the model, not the formulaMeasure the visual query that users actually runFilter arguments deserve special attentionCardinality can dominate a technically…

A lakehouse and a warehouse are not mutually exclusive choices in Microsoft Fabric. Both can store analytical data in OneLake using Delta format, but they expose different development experiences and are suited to different patterns of ingestion, transformation, governance, and consumption. Home/Microsoft/Microsoft DP-600: Lakehouse and Warehouse in One Fabric ArchitectureMicrosoftPublished October 3, 2026On this pageStart with workload shape, not product preferenceOneLake reduces the old duplication pressureA common pattern is engineering in the lakehouse and serving in the warehouseThe warehouse can also be the center of a medallion designShared data still…

Security in Fabric and Power BI becomes confusing when several controls are treated as interchangeable. Row-level security, object-level security, and workspace roles all influence what a person can do, but they operate at different layers and answer different questions. Home/Microsoft/Microsoft DP-600: RLS, OLS, and Workspace Roles Protect Different ThingsMicrosoftPublished October 3, 2026On this pageWorkspace roles are about the workspace and its itemsRLS filters rows inside the semantic modelOLS hides model objects rather than filtering their rowsRLS and OLS are not substitutes for correct workspace assignmentPermissions can be inherited through several…

Organizations rarely suffer from a shortage of metrics. They suffer from too many definitions of the same metric. Revenue, active customer, conversion, margin, retention, and service level can all acquire slightly different logic as individual reports solve local problems. Home/Microsoft/Microsoft DP-600: Build a Reusable Metrics Layer in Microsoft FabricMicrosoftPublished October 3, 2026On this pageStart with business grain before metric formulasSeparate raw fields, modeled facts, and business measuresCreate measures that compose rather than duplicateDimensions are part of the metric contractMetric ownership is as important as metric codeDesign for both governed reuse…

Fabric capacity is easy to treat as a procurement detail: choose a SKU, watch the bill, and resize when necessary. In production analytics, capacity is more fundamental. It is the shared compute boundary within which interactive queries, refreshes, pipelines, notebooks, warehouses, and other Fabric workloads compete for resources. Home/Microsoft/Microsoft DP-600: Fabric Capacity Is an Architecture ConstraintMicrosoftPublished October 3, 2026On this pageCapacity connects workloads that teams may think are separateInteractive and background operations behave differentlyUtilization above 100 percent is not the same as throttlingWorkload timing is an architecture decisionItem design determines…

Modern analytics platforms have faster engines, elastic compute, and more managed services than older BI stacks, but one old principle remains stubbornly important: do the expensive work as close to the capable data source as practical. Home/Microsoft/Microsoft DP-600: Why Query Folding Still MattersMicrosoftPublished October 3, 2026On this pageQuery folding is an execution-location decisionFolding can be full, partial, or absentFilter early because row reduction compoundsA single step can change the entire cost profileNative queries can help and can also create trade-offsDataflows make folding an operational issue, not just a desktop concernFolding…

Analytics teams need speed, but shared data products cannot be changed as casually as a personal report. A semantic model rename, warehouse schema change, security-rule edit, or broken connection can affect many downstream users at once. Home/Microsoft/Microsoft DP-600: Deployment Pipelines for Governed AnalyticsMicrosoftPublished October 3, 2026On this pageStages create separation only if workspaces are truly separatedPipeline permissions and workspace permissions are differentCompare before deploy should be part of the release habitEnvironment-specific settings need deliberate rulesSemantic models need compatibility thinkingTesting should include data, security, and performanceRelease evidence makes governance auditableAutomation helps…

Refreshing a small semantic model is simple: reload the data and replace the old copy. At enterprise scale, that approach becomes expensive because most historical rows have not changed, refresh windows collide with user activity, and a single failed full load can hold an entire model hostage. Home/Microsoft/Microsoft DP-600: Incremental Refresh and Partitioning at Enterprise ScaleMicrosoftPublished October 3, 2026On this pageIncremental refresh works by dividing time into managed partitionsRangeStart and RangeEnd must reach the source efficientlyChoose the refresh window from change behavior, not convenienceDetect-data-changes can reduce unnecessary workHistorical backfills require…

Analytics engineering is often associated with batch transformation, dimensional models, SQL, and semantic layers. Real-world analytics estates also contain event streams, telemetry, logs, clickstreams, and operational signals whose value declines if they wait for a traditional overnight pipeline. Home/Microsoft/Microsoft DP-600: KQL in an Analytics Engineering WorkflowMicrosoftPublished October 3, 2026On this pageKQL is designed around high-volume event analysisEventhouse provides the storage and query contextIngestion and transformation can happen close to the streamKQL and SQL answer overlapping but not identical needsTime windows and event grain should be explicitEnrichment connects real-time signals to…

Capacity incidents rarely begin with a clean message that says exactly which operation caused the problem. Users report that a report is slow, a refresh times out, a pipeline waits longer than usual, or an item fails with a capacity limit error. By the time the platform team investigates, the original spike may already be gone. Home/Microsoft/Microsoft DP-600: Monitor Fabric Before Capacity Becomes the ProblemMicrosoftPublished October 3, 2026On this pageStart from the exact symptom and timeCheck throttling before blaming capacityUse the compute page to find the consumerSeparate interactive and background…

Data lineage is easy to admire and surprisingly easy to ignore. A diagram can show that a report depends on a semantic model, which depends on a warehouse or lakehouse, which in turn depends on pipelines and source systems. That picture becomes valuable only when a team uses it to answer operational questions: What will break if this table changes? Who owns the downstream model? Why is a report stale? Which assets need to be tested before a release? Home/Microsoft/Microsoft DP-600: Data Lineage Only Matters When Teams Act on ItMicrosoftPublished…

Bronze, silver, and gold are useful labels because they describe increasing levels of refinement. They become less useful when a team designs the layers only around pipeline convenience. A medallion architecture succeeds when the gold layer is genuinely easier for analysts to understand, trust, and reuse than the raw and enriched data underneath it. Home/Microsoft/Microsoft DP-600: Build Medallion Layers for Analysts, Not Just EngineersMicrosoftPublished October 3, 2026On this pageBronze should preserve evidence, not convenienceSilver is where reliability becomes reusableGold should reflect how analysts ask questionsChoose lakehouse or warehouse by workload,…