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Microsoft Power BI Data Analyst Exam Certification Details:

Number of Questions	40-60
Exam Code	PL-300
Books / Training	Course PL-300T00: Microsoft Power BI Data Analyst
Duration	180 mins
Passing Score	700 / 1000
Exam Name	Microsoft Certified - Power BI Data Analyst Associate
Exam Price	$165 (USD)
Schedule Exam	Pearson VUE
Sample Questions	Microsoft Power BI Data Analyst Sample Questions

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日本語 Exam Syllabus Topics:

Section	Weight	Objectives
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. Integrate data from multiple sources 2. Configure data refresh settings 3. Define table structures and properties - Get or connect to data 1. Configure data source settings, credentials, and privacy levels 2. Identify and connect to data sources or shared semantic models 3. Create and modify parameters 4. Choose storage modes: Import, DirectQuery, DirectLake
Manage and secure Power BI	15-20%	- Manage workspaces and assets 1. Publish, update, and organize reports/datasets 2. Manage data refresh and scheduled updates 3. Create and configure workspaces - Deploy and distribute content 1. Monitor usage and performance 2. Share reports, dashboards, and apps 3. Embed content in applications or websites - Implement security and governance 1. Apply data sensitivity labels and protection 2. Configure row-level security (RLS) and object-level security 3. Manage permissions and access
Model the data	25-30%	- Design data models 1. Define tables, columns, and hierarchies 2. Create common date tables 3. Create relationships: cardinality, cross-filter direction, security 4. Implement role-playing dimensions - 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. Interpret results and identify trends 2. Implement custom visuals and R/Python scripts 3. Create and manage bookmarks and tooltips - Enhance reports with analytics 1. Use AI visuals, forecasts, and key influencers 2. Create paginated reports 3. Apply conditional formatting and custom visuals - Create reports and dashboards 1. Choose appropriate visualizations 2. Design report layout, formatting, and interactivity 3. Apply filters, slicers, and drill-through 4. Create dashboards and pinned elements

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

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