Microsoft PL-300J Questions & Answers - in .pdf
- Total Q&A: 515
- Update: Aug 04, 2026
- Price: $69.99
- Vendor: Microsoft
- Exam Code: PL-300J
- Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
- Features:
- Convenient, easy to study.
- Printable Microsoft PL-300J PDF Format.
- 100% Money Back Guarantee.
- Complete Microsoft Recommended Syllabus.
- Free PL-300J PDF Demo Available.
- Regularly Updated.
- Technical Support through Live Chat or Email.
- Exact Microsoft PL-300J Exam Questions with Correct Answers, verified by Experts with years of Experience in IT Field.
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Microsoft PL-300J Q&A - Testing Engine
- Total Q&A: 515
- Update: Aug 04, 2026
- Price: $69.99
- Vendor: Microsoft
- Exam Code: PL-300J
- Exam Name: Microsoft Power BI Data Analyst (PL-300日本語版)
- Features:
- Uses the World Class PL-300J Testing Engine.
- Real PL-300J exam questions with answers.
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Effective learning
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Skills measured
- Download the study guide in the preceding “Tip” box for more details about the skills measured on this exam.
- Deploy and maintain assets (20-25%)
- Visualize and analyze the data (25-30%)
- Model the data (30-35%)
- Prepare the data (15-20%)
Learn more about the exam
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.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300
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 using Power BI Desktop.
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 are a professional data analyst with 2-4 years of work experience or an IT professional with 2-4 years of experience.
You have at least one year of experience using Power Query in Excel, or an equivalent experience using another data analysis tool.
Microsoft PL-300日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|
| Model the Data | 25-30% | - Design a data model
- 1. Define tables and table schemas
- 2. Implement row-level security
- 3. Apply field metadata and groupings
- 4. Design a star schema or snowflake schema
- 5. Resolve performance issues with relationships
- 6. Determine the appropriate granularity
- Optimize model performance
- 1. Improve user experience by hiding objects
- 2. Optimize DirectQuery models
- 3. Validate performance and resolve issues
- 4. Configure aggregations
- 5. Optimize Dax queries
- Create measures and DAX calculations
- 1. Create calculated measures
- 2. Use Time Intelligence functions
- 3. Create semi-additive measures
- 4. Write and use basic DAX syntax
- 5. Use CALCULATE and FILTER functions
- 6. Implement context transition
- Develop the data model
- 1. Build hierarchies and hierarchical fields
- 2. Configure table relationships
- 3. Create calculated tables and columns
- 4. Implement row-level security roles
- 5. Create common date tables
- 6. Use the calculation group feature
|
| Prepare the Data | 10-15% | - Get data from various data sources
- 1. Select a shared dataset or create a local copy
- 2. Change data source settings
- 3. Use Microsoft Fabric and OneLake
- 4. Choose between DirectQuery, Import, and Dual storage modes
- 5. Configure dataset refresh
- 6. Identify and connect to a data source
- Clean, transform, and load the data
- 1. Determine proper data types
- 2. Apply user-friendly naming conventions to columns and tables
- 3. Design and build intermediate tables
- 4. Profile the data
- 5. Resolve data quality issues
- 6. Configure data loading and queries
- 7. Identify the data structure
|
| Manage and Maintain Workspace Items | 10-15% | - Manage datasets
- 1. Configure dataset metadata and properties
- 2. Manage dataset refresh scheduling
- 3. Manage gateways and data sources
- 4. Resolve dataset permission issues
- 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
|
| Visualize the Data | 25-30% | - Enrich reports with advanced visuals
- 1. Integrate Microsoft Copilot for Power BI
- 2. Configure R and Python visuals
- 3. Use dynamic page navigation
- 4. Create custom visuals
- Enhance reports for user experience
- 1. Add accessibility features and compliance
- 2. Add tooltips and navigation
- 3. Apply artistic formatting to visuals
- 4. Design for mobile and specific layouts
- Build visuals
- 1. Format and configure pages and report backgrounds
- 2. Configure visual interactions and cross-filtering
- 3. Apply AI insights and enhanced analytics
- 4. Determine the appropriate visual type
- 5. Configure data colors and shapes
- 6. Apply sorting and filtering to visuals
|
| Analyze the Data | 10-15% | - Perform analysis in Power BI
- 1. Configure auto-insights
- 2. Generate Pinn visual insights
- 3. Identify patterns and trends
- 4. Use the Q&A visual
- 5. Apply Quick Insights
- Work with metrics in Power BI
- 1. Track goals with scorecards
- 2. Create metrics using Microsoft measurements
- 3. Use the Decomposition Tree visual
- 4. Define and monitor KPIs
|
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