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Microsoft Power BI Data Analyst Certification Exam is one of the most popular certification exams in the market. However, most candidates don't pass it on their first attempt. The reasons for this are many, but the most common ones are not having enough time to prepare, not knowing where to start and what to study, or not having access to quality learning materials. To help you overcome these obstacles and pass Microsoft Power BI Data Analyst Certification Exam easily, our experts have created a comprehensive Microsoft PL-300 Dumps that will give you everything you need to know to pass Microsoft Power BI Data Analyst Certification Exam quickly and efficiently.

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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

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

Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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