Microsoft PL-300 Deutsch dumps - in .pdf

PL-300 Deutsch pdf
  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Sep 02, 2026
  • Q & A: 472 Questions and Answers
  • PDF Price: $69.99
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  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Sep 02, 2026
  • Q & A: 472 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
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Microsoft PL-300 Deutsch dumps - Testing Engine

PL-300 Deutsch Testing Engine
  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Sep 02, 2026
  • Q & A: 472 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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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

  • United States; USD 90,000

  • India; INR 500,000

  • Australia; AUD 75,000

  • United Kingdom; POUNDS 60,000

Prerequisites of Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam is a test which assesses your ability to have a high-level understanding of the data analysis process, including collecting, analyzing and visualizing data. It is a certification that will help you gain the required skills to be able to work with business intelligence solutions and tools. To be eligible to take this exam, you must meet the following prerequisites:

  • You have at least one year of experience working with relational databases, such as SQL Server or Oracle. In addition, you should have a basic understanding of how to create queries and reports using SQL Server Management Studio or Toad Data Point.

  • You have at least one year of experience using Power BI Desktop.

  • You have at least one year of experience using Power Query in Excel, or an equivalent experience using another data analysis tool.

  • You are a professional data analyst with 2-4 years of work experience or an IT professional with 2-4 years of experience.

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

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.

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

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Visualize the Data25-30%- Build visuals
  • 1. Apply AI insights and enhanced analytics
  • 2. Configure data colors and shapes
  • 3. Apply sorting and filtering to visuals
  • 4. Determine the appropriate visual type
  • 5. Format and configure pages and report backgrounds
  • 6. Configure visual interactions and cross-filtering
- Enhance reports for user experience
  • 1. Add tooltips and navigation
  • 2. Add accessibility features and compliance
  • 3. Apply artistic formatting to visuals
  • 4. Design for mobile and specific layouts
- Enrich reports with advanced visuals
  • 1. Create custom visuals
  • 2. Configure R and Python visuals
  • 3. Integrate Microsoft Copilot for Power BI
  • 4. Use dynamic page navigation
Model the Data25-30%- Develop the data model
  • 1. Use the calculation group feature
  • 2. Create common date tables
  • 3. Configure table relationships
  • 4. Implement row-level security roles
  • 5. Create calculated tables and columns
  • 6. Build hierarchies and hierarchical fields
- Design a data model
  • 1. Design a star schema or snowflake schema
  • 2. Resolve performance issues with relationships
  • 3. Define tables and table schemas
  • 4. Implement row-level security
  • 5. Apply field metadata and groupings
  • 6. Determine the appropriate granularity
- Optimize model performance
  • 1. Validate performance and resolve issues
  • 2. Optimize DirectQuery models
  • 3. Improve user experience by hiding objects
  • 4. Configure aggregations
  • 5. Optimize Dax queries
- Create measures and DAX calculations
  • 1. Implement context transition
  • 2. Create calculated measures
  • 3. Write and use basic DAX syntax
  • 4. Create semi-additive measures
  • 5. Use CALCULATE and FILTER functions
  • 6. Use Time Intelligence functions
Analyze the Data10-15%- Perform analysis in Power BI
  • 1. Configure auto-insights
  • 2. Identify patterns and trends
  • 3. Generate Pinn visual insights
  • 4. Use the Q&A visual
  • 5. Apply Quick Insights
- Work with metrics in Power BI
  • 1. Create metrics using Microsoft measurements
  • 2. Define and monitor KPIs
  • 3. Use the Decomposition Tree visual
  • 4. Track goals with scorecards
Prepare the Data10-15%- Clean, transform, and load the data
  • 1. Resolve data quality issues
  • 2. Configure data loading and queries
  • 3. Determine proper data types
  • 4. Design and build intermediate tables
  • 5. Apply user-friendly naming conventions to columns and tables
  • 6. Profile the data
  • 7. Identify the data structure
- Get data from various data sources
  • 1. Choose between DirectQuery, Import, and Dual storage modes
  • 2. Change data source settings
  • 3. Use Microsoft Fabric and OneLake
  • 4. Select a shared dataset or create a local copy
  • 5. Configure dataset refresh
  • 6. Identify and connect to a data source
Manage and Maintain Workspace Items10-15%- Create and manage workspaces
  • 1. Publish and update a Power BI app
  • 2. Configure workspace membership and roles
  • 3. Endorse sensitive content with sensitivity labels
  • 4. Configure content certification
- Manage datasets
  • 1. Manage dataset refresh scheduling
  • 2. Configure dataset metadata and properties
  • 3. Resolve dataset permission issues
  • 4. Manage gateways and data sources

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