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: Aug 12, 2026

Q & A: 515 Questions and Answers

PL-300日本語 Free Demo download

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

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What is the salary of the Microsoft Power BI Data Analyst Certified professional

The Average salary of different countries of Microsoft Power BI Data Analyst certified professionals:

Canada; CAD 70,000
India; INR 500,000
United Kingdom; POUNDS 60,000
United States; USD 90,000
Australia; AUD 75,000

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Microsoft PL-300日本語 Exam Syllabus Topics:

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

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