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Microsoft Power BI Data Analyst Certification Exam Reference

Passing Score, Duration & Questions For Microsoft PL-300 Exam

Time Duration: 180 minutes
Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian
The passing score: 700
Number of Questions: 40-60 questions

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

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Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: prepare the data; model the data; visualize and analyze the data; and deploy and maintain assets.

Microsoft PL-300 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Model the Data	25-30%	- Optimize model performance 1. Validate performance and resolve issues 2. Improve user experience by hiding objects 3. Optimize DirectQuery models 4. Optimize Dax queries 5. Configure aggregations - Develop the data model 1. Create calculated tables and columns 2. Build hierarchies and hierarchical fields 3. Implement row-level security roles 4. Configure table relationships 5. Create common date tables 6. Use the calculation group feature - Design a data model 1. Resolve performance issues with relationships 2. Apply field metadata and groupings 3. Implement row-level security 4. Design a star schema or snowflake schema 5. Determine the appropriate granularity 6. Define tables and table schemas - Create measures and DAX calculations 1. Create semi-additive measures 2. Use CALCULATE and FILTER functions 3. Create calculated measures 4. Use Time Intelligence functions 5. Implement context transition 6. Write and use basic DAX syntax
Topic 2: Prepare the Data	10-15%	- Get data from various data sources 1. Configure dataset refresh 2. Select a shared dataset or create a local copy 3. Choose between DirectQuery, Import, and Dual storage modes 4. Identify and connect to a data source 5. Change data source settings 6. Use Microsoft Fabric and OneLake - Clean, transform, and load the data 1. Identify the data structure 2. Profile the data 3. Resolve data quality issues 4. Determine proper data types 5. Design and build intermediate tables 6. Configure data loading and queries 7. Apply user-friendly naming conventions to columns and tables
Topic 3: Analyze the Data	10-15%	- 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. Use the Q&A visual 3. Apply Quick Insights 4. Identify patterns and trends 5. Generate Pinn visual insights
Topic 4: Manage and Maintain Workspace Items	10-15%	- Create and manage workspaces 1. Configure workspace membership and roles 2. Publish and update a Power BI app 3. Configure content certification 4. Endorse sensitive content with sensitivity labels - Manage datasets 1. Configure dataset metadata and properties 2. Manage gateways and data sources 3. Manage dataset refresh scheduling 4. Resolve dataset permission issues
Topic 5: Visualize the Data	25-30%	- Build visuals 1. Apply AI insights and enhanced analytics 2. Configure data colors and shapes 3. Apply sorting and filtering to visuals 4. Format and configure pages and report backgrounds 5. Configure visual interactions and cross-filtering 6. Determine the appropriate visual type - 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 - 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