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Exam PL-300: Microsoft Power BI Data Analyst

The Power BI data analyst delivers actionable insights by leveraging available data and applying domain expertise. The Power BI data analyst collaborates with key stakeholders across verticals to identify business requirements, cleans and transforms the data, and then designs and builds data models by using Power BI. The Power BI data analyst provides meaningful business value through easy-to-comprehend data visualizations, enables others to perform self-service analytics, and deploys and configures solutions for consumption. Candidates for this exam should be proficient using Power Query and writing expressions by using DAX.

Passing score: 700. Learn more about exam scores.

Part of the requirements for: Microsoft Certified: Power BI Data Analyst Associate

For more info visit:

Microsoft Power BI Data Analyst Certification Exam Reference

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300

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Microsoft PL-300 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prepare the Data10-15%- Clean, transform, and load the data
  • 1. Apply user-friendly naming conventions to columns and tables
  • 2. Resolve data quality issues
  • 3. Design and build intermediate tables
  • 4. Determine proper data types
  • 5. Identify the data structure
  • 6. Profile the data
  • 7. Configure data loading and queries
- Get data from various data sources
  • 1. Choose between DirectQuery, Import, and Dual storage modes
  • 2. Change data source settings
  • 3. Use Microsoft Fabric and OneLake
  • 4. Configure dataset refresh
  • 5. Identify and connect to a data source
  • 6. Select a shared dataset or create a local copy
Topic 2: Model the Data25-30%- Create measures and DAX calculations
  • 1. Create semi-additive measures
  • 2. Use CALCULATE and FILTER functions
  • 3. Create calculated measures
  • 4. Write and use basic DAX syntax
  • 5. Implement context transition
  • 6. Use Time Intelligence functions
- Design a data model
  • 1. Determine the appropriate granularity
  • 2. Apply field metadata and groupings
  • 3. Resolve performance issues with relationships
  • 4. Define tables and table schemas
  • 5. Implement row-level security
  • 6. Design a star schema or snowflake schema
- Develop the data model
  • 1. Create common date tables
  • 2. Configure table relationships
  • 3. Implement row-level security roles
  • 4. Build hierarchies and hierarchical fields
  • 5. Use the calculation group feature
  • 6. Create calculated tables and columns
- Optimize model performance
  • 1. Configure aggregations
  • 2. Validate performance and resolve issues
  • 3. Improve user experience by hiding objects
  • 4. Optimize DirectQuery models
  • 5. Optimize Dax queries
Topic 3: Manage and Maintain Workspace Items10-15%- Manage datasets
  • 1. Configure dataset metadata and properties
  • 2. Resolve dataset permission issues
  • 3. Manage dataset refresh scheduling
  • 4. Manage gateways and data sources
- Create and manage workspaces
  • 1. Endorse sensitive content with sensitivity labels
  • 2. Configure content certification
  • 3. Publish and update a Power BI app
  • 4. Configure workspace membership and roles
Topic 4: Visualize the Data25-30%- Enhance reports for user experience
  • 1. Apply artistic formatting to visuals
  • 2. Add accessibility features and compliance
  • 3. Design for mobile and specific layouts
  • 4. Add tooltips and navigation
- Enrich reports with advanced visuals
  • 1. Create custom visuals
  • 2. Integrate Microsoft Copilot for Power BI
  • 3. Use dynamic page navigation
  • 4. Configure R and Python visuals
- Build visuals
  • 1. Format and configure pages and report backgrounds
  • 2. Apply AI insights and enhanced analytics
  • 3. Configure data colors and shapes
  • 4. Configure visual interactions and cross-filtering
  • 5. Determine the appropriate visual type
  • 6. Apply sorting and filtering to visuals
Topic 5: Analyze the Data10-15%- Work with metrics in Power BI
  • 1. Track goals with scorecards
  • 2. Use the Decomposition Tree visual
  • 3. Define and monitor KPIs
  • 4. Create metrics using Microsoft measurements
- Perform analysis in Power BI
  • 1. Configure auto-insights
  • 2. Generate Pinn visual insights
  • 3. Identify patterns and trends
  • 4. Apply Quick Insights
  • 5. Use the Q&A visual

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