Microsoft Power BI Data Analyst (PL-300 Deutsch Version) : PL-300 Deutsch

Exam Code: PL-300-Deutsch
Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
Updated: Aug 06, 2026
Q & A: 515 Questions and Answers

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About Microsoft PL-300 Deutsch Exam

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.

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

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

Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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