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Microsoft PL-300 Exam Syllabus Topics:
| Section |
Weight |
Objectives |
| Topic 1: Model the data |
25-30% |
– Optimize model performance
- 1. Use aggregations and composite models
- 2. Reduce cardinality and data size
- 3. Optimize relationships and calculations
– Design data models
- 1. Define tables, columns, and hierarchies
- 2. Implement role-playing dimensions
- 3. Create relationships: cardinality, cross-filter direction, security
- 4. Create common date tables
– Create model calculations
- 1. Implement aggregation and time intelligence
- 2. Use CALCULATE and filter context
- 3. Use DAX: calculated columns, calculated tables, measures
|
| Topic 2: Manage and secure Power BI |
15-20% |
– Deploy and distribute content
- 1. Monitor usage and performance
- 2. Share reports, dashboards, and apps
- 3. Embed content in applications or websites
– Manage workspaces and assets
- 1. Publish, update, and organize reports/datasets
- 2. Manage data refresh and scheduled updates
- 3. Create and configure workspaces
– Implement security and governance
- 1. Configure row-level security (RLS) and object-level security
- 2. Apply data sensitivity labels and protection
- 3. Manage permissions and access
|
| Topic 3: Visualize and analyze data |
25-30% |
– Enhance reports with analytics
- 1. Use AI visuals, forecasts, and key influencers
- 2. Create paginated reports
- 3. Apply conditional formatting and custom visuals
– Perform data analysis
- 1. Implement custom visuals and R/Python scripts
- 2. Interpret results and identify trends
- 3. Create and manage bookmarks and tooltips
– Create reports and dashboards
- 1. Design report layout, formatting, and interactivity
- 2. Create dashboards and pinned elements
- 3. Apply filters, slicers, and drill-through
- 4. Choose appropriate visualizations
|
| Topic 4: Prepare the data |
25-30% |
– Profile and clean data
- 1. Evaluate data statistics and column properties
- 2. Resolve inconsistencies, null values, and errors
- 3. Transform data using Power Query Editor
- 4. Manage data types, columns, and rows
– Load and configure data
- 1. Define table structures and properties
- 2. Integrate data from multiple sources
- 3. Configure data refresh settings
– Get or connect to data
- 1. Create and modify parameters
- 2. Identify and connect to data sources or shared semantic models
- 3. Choose storage modes: Import, DirectQuery, DirectLake
- 4. Configure data source settings, credentials, and privacy levels
|

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