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The need for this exam has increased tremendously over the years. As more people start using technology, there is a greater need for more professionals who can help them with their problems. With the increasing demand for people with these skills, it will be difficult for you to get a job without having one. If you want to succeed in your career, you should consider taking this test because it will give you an edge over other candidates who do not have it. It will also help you stand out from the crowd if you are applying for jobs online or even if you are looking for promotion within your company. Column data types have questions and answers subcategories for real time scenario. Sample questions about data source settings have calculated columns mobile view. Quick measure mode filters the app syllabus to practice the average sales. If you are feeling sensitive to additives in your food, you may want to format your schema prepared environment to be more additive-sensitive. This could involve avoiding foods that contain additives, eating organic foods whenever possible, or using natural sweeteners.
Microsoft PL-300 Exam Overview:
| Certification Vendor: | Microsoft |
| Exam Name: | Microsoft Power BI Data Analyst |
| Exam Number: | PL-300 |
| Exam Format: | Multiple choice, Case study, Drag and drop, Short answer |
| Exam Price: | $165.00 USD |
| Passing Score: | 700 (scaled score, passing not publicly disclosed) |
| Real Exam Qty: | 40-60 |
| Available Languages: | English, Japanese, Chinese (Simplified), Korean |
| Exam Duration: | 120 minutes |
| Certificate Validity Period: | 1 year |
| Related Certifications: | Microsoft Certified: Power BI Data Analyst Associate |
| Sample Questions: | Microsoft PL-300 Sample Questions |
| Exam Way: | Online proctored exam (Pearson VUE) or in-person testing center |
| Pre Condition: | No mandatory prerequisites, but Microsoft recommends having foundational knowledge of data concepts and Microsoft Power BI before taking the exam. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/certifications/exams/pl-300/ |
Benefits
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. Itbraindumps Microsoft PL-300 Dumps will help you to pass your certification exam and get highly paid job.
Microsoft Power BI Data Analyst Exam Certification Details:
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300
Microsoft PL-300 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Visualize the Data | 25-30% | - Enrich reports with advanced visuals
- 1. Create custom visuals
- 2. Integrate Microsoft Copilot for Power BI
- 3. Use dynamic page navigation
- 4. Configure R and Python visuals
- 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
- Build visuals
- 1. Determine the appropriate visual type
- 2. Apply sorting and filtering to visuals
- 3. Format and configure pages and report backgrounds
- 4. Apply AI insights and enhanced analytics
- 5. Configure visual interactions and cross-filtering
- 6. Configure data colors and shapes
|
| Prepare the Data | 10-15% | - Get data from various data sources
- 1. Identify and connect to a data source
- 2. Choose between DirectQuery, Import, and Dual storage modes
- 3. Select a shared dataset or create a local copy
- 4. Change data source settings
- 5. Configure dataset refresh
- 6. Use Microsoft Fabric and OneLake
- Clean, transform, and load the data
- 1. Identify the data structure
- 2. Profile the data
- 3. Apply user-friendly naming conventions to columns and tables
- 4. Resolve data quality issues
- 5. Determine proper data types
- 6. Design and build intermediate tables
- 7. Configure data loading and queries
|
| Model the Data | 25-30% | - Create measures and DAX calculations
- 1. Use CALCULATE and FILTER functions
- 2. Create calculated measures
- 3. Implement context transition
- 4. Create semi-additive measures
- 5. Write and use basic DAX syntax
- 6. Use Time Intelligence functions
- Design a data model
- 1. Implement row-level security
- 2. Apply field metadata and groupings
- 3. Determine the appropriate granularity
- 4. Resolve performance issues with relationships
- 5. Define tables and table schemas
- 6. Design a star schema or snowflake schema
- Develop the data model
- 1. Build hierarchies and hierarchical fields
- 2. Implement row-level security roles
- 3. Configure table relationships
- 4. Use the calculation group feature
- 5. Create calculated tables and columns
- 6. Create common date tables
- Optimize model performance
- 1. Optimize Dax queries
- 2. Configure aggregations
- 3. Validate performance and resolve issues
- 4. Optimize DirectQuery models
- 5. Improve user experience by hiding objects
|
| Manage and Maintain Workspace Items | 10-15% | - Create and manage workspaces
- 1. Publish and update a Power BI app
- 2. Endorse sensitive content with sensitivity labels
- 3. Configure workspace membership and roles
- 4. Configure content certification
- Manage datasets
- 1. Resolve dataset permission issues
- 2. Configure dataset metadata and properties
- 3. Manage gateways and data sources
- 4. Manage dataset refresh scheduling
|
| Analyze the Data | 10-15% | - Work with metrics in Power BI
- 1. Create metrics using Microsoft measurements
- 2. Use the Decomposition Tree visual
- 3. Track goals with scorecards
- 4. Define and monitor KPIs
- Perform analysis in Power BI
- 1. Identify patterns and trends
- 2. Generate Pinn visual insights
- 3. Use the Q&A visual
- 4. Configure auto-insights
- 5. Apply Quick Insights
|
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