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This exam measures your ability to accomplish the following technical tasks: prepare the data; model the data; visualize and analyze the data; and deploy and maintain assets.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300
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The Microsoft Power BI Data Analyst certification is a globally recognized certification that validates your ability to design, build, and optimize data models using Power BI. It also demonstrates your expertise in building queries and reports with appropriate visuals, including dashboards, scorecards, and visualizations. This certification focuses on the intermediate-level skills required for data modeling and analysis.
The Microsoft Power BI Data Analyst certification provides many benefits to you. It helps you boost your career growth by validating your knowledge in building business intelligence solutions using Power BI platform. It validates your skills in designing reports and visualizations for various business needs. It increases your credibility among employers as most companies look for professionals who have this certification. It provides an opportunity to earn a higher salary package compared to those without this certification. ExamcollectionPass Microsoft PL-300 Dumps will help you to pass your certification exam and get highly paid job.
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Microsoft PL-300 Deutsch Exam Syllabus Topics:
| Section | Weight | Objectives |
| Model the Data | 25-30% | - Optimize model performance
- 1. Validate performance and resolve issues
- 2. Improve user experience by hiding objects
- 3. Configure aggregations
- 4. Optimize DirectQuery models
- 5. Optimize Dax queries
- Design a data model
- 1. Resolve performance issues with relationships
- 2. Define tables and table schemas
- 3. Apply field metadata and groupings
- 4. Implement row-level security
- 5. Determine the appropriate granularity
- 6. Design a star schema or snowflake schema
- Develop the data model
- 1. Implement row-level security roles
- 2. Create common date tables
- 3. Use the calculation group feature
- 4. Configure table relationships
- 5. Build hierarchies and hierarchical fields
- 6. Create calculated tables and columns
- Create measures and DAX calculations
- 1. Create semi-additive measures
- 2. Create calculated measures
- 3. Write and use basic DAX syntax
- 4. Implement context transition
- 5. Use CALCULATE and FILTER functions
- 6. Use Time Intelligence functions
|
| Visualize the Data | 25-30% | - Build visuals
- 1. Configure data colors and shapes
- 2. Apply sorting and filtering to visuals
- 3. Configure visual interactions and cross-filtering
- 4. Apply AI insights and enhanced analytics
- 5. Determine the appropriate visual type
- 6. Format and configure pages and report backgrounds
- Enrich reports with advanced visuals
- 1. Create custom visuals
- 2. Configure R and Python visuals
- 3. Use dynamic page navigation
- 4. Integrate Microsoft Copilot for Power BI
- Enhance reports for user experience
- 1. Add accessibility features and compliance
- 2. Design for mobile and specific layouts
- 3. Add tooltips and navigation
- 4. Apply artistic formatting to visuals
|
| 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
|
| Prepare the Data | 10-15% | - Get data from various data sources
- 1. Identify and connect to a data source
- 2. Use Microsoft Fabric and OneLake
- 3. Change data source settings
- 4. Configure dataset refresh
- 5. Choose between DirectQuery, Import, and Dual storage modes
- 6. Select a shared dataset or create a local copy
- Clean, transform, and load the data
- 1. Determine proper data types
- 2. Profile the data
- 3. Configure data loading and queries
- 4. Design and build intermediate tables
- 5. Identify the data structure
- 6. Apply user-friendly naming conventions to columns and tables
- 7. Resolve data quality issues
|
| Analyze the Data | 10-15% | - Work with metrics in Power BI
- 1. Use the Decomposition Tree visual
- 2. Track goals with scorecards
- 3. Define and monitor KPIs
- 4. Create metrics using Microsoft measurements
- Perform analysis in Power BI
- 1. Identify patterns and trends
- 2. Apply Quick Insights
- 3. Configure auto-insights
- 4. Use the Q&A visual
- 5. Generate Pinn visual insights
|