PL-300 Prep by Melarks
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PL-300 Exam Cheat Sheet

A compact scan of the distinctions, formulas and Service features worth having fresh in your mind before the exam.

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Use this for review, not first-time learning. If a bullet feels unfamiliar, return to the relevant study module and answer its exam checks.

Prepare the Data

  • Import = in-memory copy; DirectQuery = source queried at interaction time; DirectLake = Fabric/OneLake storage mode.
  • Profile beyond the top 1,000 rows when uniqueness/quality conclusions matter.
  • Correct data type first; use locale-aware conversion for ambiguous dates/numbers.
  • Append adds rows. Merge joins columns by key. Left Anti returns unmatched left rows.
  • Reference inherits upstream query changes; Duplicate is an independent copy of steps.
  • Unpivot turns columns into attribute/value rows; Unpivot Other Columns is resilient to new period columns.
  • Remove unused rows/columns early and preserve query folding where possible.
  • Incremental refresh: Date/Time RangeStart + RangeEnd, commonly >= RangeStart and < RangeEnd.
  • Enable Load controls whether a query becomes a model table; refresh participation is a separate setting.
  • Privacy levels govern source isolation during combination; they are not RLS.

Data Modeling

  • Prefer a star schema: dimensions on the 1 side, fact table on the many side.
  • Define grain first: what exactly does one fact-table row represent?
  • Single-direction dimension → fact is the default best practice; bidirectional is a deliberate exception.
  • Many-to-many business relationships often need a bridge table.
  • Inactive relationships can be activated inside CALCULATE with USERELATIONSHIP.
  • Use role-playing date dimensions when independent Order Date and Ship Date slicers are required.
  • Date table: unique, non-null, contiguous date column; mark it as Date Table where appropriate.
  • Month Name sorts by Month Number; Month-Year needs a sequential YearMonth key.
  • Measures are dynamic filter-context calculations; calculated columns are stored row-level values.
  • High-cardinality unused text/IDs are common model-size targets. Hiding a column does not reduce model size.

DAX & Filter Context

  • Measures already respond to filter context. CALCULATE is for changing context, not merely 'making filters work'.
  • Row context = current row; filter context = visible subset from visuals, slicers, filters and relationships.
  • CALCULATE modifies filter context and performs context transition when row context exists.
  • REMOVEFILTERS(Column) removes only that column's filter; unrelated filters remain.
  • KEEPFILTERS intersects a new same-column filter with the existing filter.
  • SUMX/AVERAGEX iterate a table; SUM/AVERAGE aggregate existing columns.
  • VALUES(Column) returns distinct visible values; useful for entity-grain averages.
  • DIVIDE is safer than / when denominator can be zero or blank.
  • SAMEPERIODLASTYEAR shifts the current date set one year; DATEADD shifts by a chosen interval.
  • Variables store results in the context where they are evaluated; they do not magically recalculate after a later context change.
  • Balances are often semi-additive: aggregate across entities, but use a closing/last-data-date logic across time.
  • Calculation groups reuse transformations across measures; SELECTEDMEASURE identifies the current measure.
  • DAX Query View uses queries such as EVALUATE to inspect model results.

Visualize & Analyze

  • Line = trend; bar/column = category comparison; scatter = numeric relationship; matrix = hierarchy/crosstab.
  • Gauge = value vs target/range. KPI = status/trend with target over time.
  • Filter restricts a target visual; Highlight keeps broader context and emphasizes a subset.
  • Drill down stays within a hierarchy; Drillthrough navigates to a detail page with context.
  • Report page tooltip shows rich hover content without navigation.
  • Bookmarks can capture Data, Display and Current page; avoid Data when a bookmark should only show/hide visuals.
  • Top N requires a value measure; sorting descending alone does not limit rows.
  • Field parameter switches fields/measures; What-if parameter provides numeric scenario input.
  • Key influencers ranks factors associated with an outcome; decomposition tree breaks a measure across dimensions.
  • Q&A = user asks natural language. Smart narrative = Power BI generates text.
  • Analytics features can include reference lines, forecasting, anomaly/outlier detection, clustering and error bars.
  • Paginated reports are RDL, authored in Power BI Report Builder, and optimized for pixel-perfect/print/multi-page output.
  • Visual calculations operate on a visual's result structure and are not reusable semantic-model measures.
  • Accessibility: alt text, tab order, contrast, labels/icons—never rely on color alone.

Power BI Service, Security & Governance

  • Workspace = collaboration/authoring. App = curated distribution to consumers.
  • Viewer is the typical workspace role when RLS must constrain a user; elevated editors are not constrained the same way.
  • Build permission allows creating reports/Analyze in Excel from a semantic model; Reshare allows passing access onward.
  • Dynamic RLS commonly uses a user-access mapping table + USERPRINCIPALNAME().
  • Multiple RLS roles are additive (union/OR), not restrictive AND.
  • OLS protects model objects such as tables/columns; hiding fields is not security.
  • Dashboard = single-page Service canvas. Tiles are pinned/supported dashboard items and can link back to source reports.
  • App audiences control which content is visible; RLS controls which data rows are visible.
  • Gateway provides Service-to-on-prem connectivity; source credentials are separate.
  • Scheduled refresh updates imported data; automatic page refresh periodically re-queries supported DirectQuery pages.
  • Subscriptions deliver content on a schedule/condition. Data alerts are threshold-based notifications in supported dashboard scenarios.
  • Usage metrics = adoption. Performance Analyzer = slow visual/DAX diagnosis.
  • Lineage/impact analysis = downstream dependencies. Query Dependencies = Power Query query/source dependencies.
  • Promoted = recommended. Certified = formally reviewed/authoritative.
  • Sensitivity labels classify/protect content; they do not replace RLS.
  • Publishing deploys report/model design changes; refresh only updates data in an existing model.
  • Deployment pipelines support Dev → Test → Prod lifecycle.

High-Value Exam Gotchas

  • Hide ≠ remove; hide ≠ security.
  • Append = rows; Merge = columns.
  • Refresh ≠ publish.
  • Gateway online ≠ source credentials valid.
  • Usage metrics ≠ Performance Analyzer.
  • Query Dependencies ≠ Lineage view.
  • Dashboard ≠ report.
  • App audience ≠ RLS.
  • Workspace role ≠ semantic-model Build permission.
  • Q&A ≠ Smart narrative.
  • Sort descending ≠ Top N.
  • Drill down ≠ Drillthrough.
  • Calculated column ≠ measure.
  • Power Query parameter ≠ What-if parameter ≠ Field parameter.
  • Paginated report ≠ ordinary interactive PBIX report.
  • Raw mock percentage ≠ Microsoft's scaled certification score.