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Cheat sheet

PL-300 Cheat Sheet

Practice this exam

Prepare Data

  • 25-30% of exam
  • Data Sources Power Query Storage Modes Data Profiling Query Folding

Model Data

  • 25-30% of exam
  • Star Schema Relationships DAX Time Intelligence Performance

Visualize + Analyze

  • 25-30% of exam
  • Reports Bookmarks AI Visuals Copilot Accessibility

Manage + Secure

  • 15-20% of exam
  • Workspaces Apps Refresh RLS Sensitivity Labels

Quick Facts

  • Exam PL-300
  • Credential Data Analyst
  • Time 100 min
  • Pass 700/1000
  • Product Power BI
  • Renewal 12 months
  • Blueprint Apr 20 2026

Mode Memory PR

  • Import caches; DirectQuery asks source
  • Import: fast DirectQuery: fresh Direct Lake: Fabric

Import vs DirectQuery PR

Import

  • Cached data
  • Fast visuals
  • Scheduled refresh

DirectQuery

  • Live source
  • Source load
  • Query limits
  • Speed vs freshness

Mode Picker PR

  • Need fastest visuals → Import
  • Need live source → DirectQuery
  • Fabric lakehouse → Direct Lake
  • Mixed mode needed → Composite model
  • Large history → Incremental refresh
  • On-prem source → Gateway

Data Sources PR

  • SQL Server Relational source
  • Excel File source
  • SharePoint Cloud files
  • Dataflow Reusable ETL
  • Dataverse Business data
  • Semantic model Shared model
  • Gateway On-prem bridge

DirectQuery vs Direct Lake PR

DirectQuery

  • Queries source
  • Many sources
  • SQL generated

Direct Lake

  • Fabric lake
  • Delta tables
  • No import
  • Source query vs lake

Transform Picker PR

  • Combine columns → Merge queries
  • Stack same schema → Append queries
  • Wide repeated columns → Unpivot
  • Rows become columns → Pivot
  • Shared base query → Reference
  • Independent branch → Duplicate

Power Query PR

  • M Query language
  • Applied steps Transform history
  • Merge Join columns
  • Append Stack rows
  • Pivot Rows to columns
  • Unpivot Columns to rows
  • Reference Dependent query
  • Duplicate Independent copy

Merge vs Append PR

Merge

  • Adds columns
  • Join keys
  • Lookup style

Append

  • Adds rows
  • Same schema
  • Union style
  • Columns vs rows

Storage Modes PR

  • Import In-memory cache
  • DirectQuery Source query
  • Direct Lake Lakehouse tables
  • Dual Import or DirectQuery
  • Composite Mixed sources
  • Incremental refresh Partitioned refresh
  • Query folding Source executes

Model Flow MO

  • Facts measure; dimensions filter
  • Facts: events Dimensions: attributes Star: preferred

Measure vs Column MO

Measure

  • Aggregates
  • Filter context
  • Visual time

Column

  • Row value
  • Stored data
  • Model size
  • Dynamic vs stored

DAX Picker MO

  • Aggregate at visual → Measure
  • Store row value → Calculated column
  • Change filter context → CALCULATE
  • Iterate rows → X function
  • Avoid divide errors → DIVIDE
  • Time shift → DATEADD

Model Design MO

  • Fact table Events/measures
  • Dimension table Descriptive attributes
  • Star schema Facts plus dimensions
  • Cardinality Relationship shape
  • Cross-filter Filter direction
  • Date table Time intelligence
  • Hierarchy Drill path
  • Role-playing Repeated dimension

DAX Context MO

  • Measures live in filter context
  • Row context Filter context CALCULATE changes

DAX MO

  • Measure Query-time calc
  • Column Row-time calc
  • CALCULATE Modify filters
  • SUMX Row iterator
  • ALL Remove filters
  • RELATED Lookup related
  • DATEADD Shift dates
  • DIVIDE Safe division

Performance MO

  • Cardinality Distinct values
  • Granularity Detail level
  • Aggregations Precomputed summaries
  • Performance Analyzer Visual timings
  • DAX query view Query testing
  • Unused columns Remove them
  • Bi-directional Use sparingly

Visuals VI

  • Bar chart Category compare
  • Line chart Trend over time
  • Card Single KPI
  • Matrix Grouped table
  • Slicer User filter
  • Tooltip Hover detail
  • Theme Report styling

Analysis VI

  • Analyze Explain increase
  • Key influencers Driver analysis
  • Decomposition tree Drill drivers
  • Q&A Natural language
  • Forecast Future trend
  • Outliers Unusual points
  • Copilot Narrative/report help

Share Stack MA

  • Workspace builds; app ships
  • Workspace: creators App: consumers Share: ad hoc

RLS vs OLS MA

RLS

  • Filters rows
  • User-specific data
  • Role rules

OLS

  • Hides objects
  • Tables/columns
  • Metadata security
  • Rows vs objects

Sharing Picker MA

  • Team authoring → Workspace
  • Broad distribution → App
  • Single recipient → Share
  • Scheduled email → Subscription
  • Certified source → Endorsement
  • Data restriction → RLS

Workspace Assets MA

  • Workspace Collaboration container
  • App Packaged distribution
  • Report Interactive pages
  • Dashboard Pinned tiles
  • Semantic model Dataset model
  • Subscription Email schedule
  • Alert Threshold notification

Workspace vs App MA

Workspace

  • Build content
  • Role access
  • Collaboration

App

  • Consume content
  • Packaged view
  • Audience targeting
  • Author vs distribute

Security MA

  • Viewer Read content
  • Contributor Edit content
  • Member Publish app
  • Admin Full workspace
  • RLS Row filtering
  • OLS Object hiding
  • Sensitivity label Data classification
  • Endorsement Promote/certify

Common Traps

Measure vs column

  • Measure aggregates ≠ Column stores rows

Merge vs append

  • Merge adds columns ≠ Append adds rows

RLS vs OLS

  • RLS filters rows ≠ OLS hides objects

Workspace vs app

  • Workspace authors ≠ App distributes

DirectQuery tradeoff

  • Fresh data ≠ Slower visuals

Gateway need

  • On-prem refresh ≠ Cloud bridge

Last Minute

  • 1. Weights: 25-30 / 25-30 / 25-30 / 15-20
  • 2. Power Query = prepare data
  • 3. Star schema beats snowflake
  • 4. Measures aggregate at query time
  • 5. Columns increase model size
  • 6. Merge columns; append rows
  • 7. Import fast; DirectQuery fresh
  • 8. RLS rows; OLS objects
  • 9. Workspace builds; app distributes
  • 10. Gateway bridges on-prem sources

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