Microsoft Power BI Data Analyst (PL-300日本語版) : PL-300日本語

Exam Code: PL-300J
Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
Updated: Oct 07, 2026
Q & A: 472 Questions and Answers

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Understanding Microsoft Power BI Data Analyst Certification Exam Topics

Microsoft Power BI Data Analyst Certification Exam Topics are below:

Deploy and maintain assets (20-25%)
Prepare the data (15-20%)
Model the data (30-35%)
Visualize and analyze the data (25-30%)

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

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Microsoft Power BI Data Analyst Certification Exam Reference

Microsoft PL-300日本語 Exam Syllabus Topics:

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

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