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The Microsoft PL-300-KR exam itself covers a range of topics, including data modeling, data visualization, data transformation, and data integration. Candidates are expected to be familiar with the various tools and features of Power BI, and to be able to use them to solve real-world business problems. PL-300-KR exam is comprised of multiple-choice questions, and candidates have two hours to complete it. Those who pass the exam will receive a Microsoft Certified: Power BI Data Analyst Associate certification, which can help them to advance their careers as data analysts.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300
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Microsoft Power BI Data Analyst is a certification exam that is designed to test the skills and knowledge of professionals who work with Power BI. PL-300-KR exam is intended for individuals who have a good understanding of the Microsoft Power BI platform and have experience working with data to create reports and visualizations. PL-300-KR exam is designed to test the ability of candidates to use Power BI to analyze and visualize data, create dashboards, and share insights with others.
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Microsoft PL-300 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
| Topic 1: Prepare the data | 25-30% | - Load and configure data
- 1. Define table structures and properties
- 2. Configure data refresh settings
- 3. Integrate data from multiple sources
- Profile and clean data
- 1. Manage data types, columns, and rows
- 2. Resolve inconsistencies, null values, and errors
- 3. Evaluate data statistics and column properties
- 4. Transform data using Power Query Editor
- Get or connect to data
- 1. Create and modify parameters
- 2. Configure data source settings, credentials, and privacy levels
- 3. Choose storage modes: Import, DirectQuery, DirectLake
- 4. Identify and connect to data sources or shared semantic models
|
| Topic 2: Visualize and analyze data | 25-30% | - Perform data analysis
- 1. Create and manage bookmarks and tooltips
- 2. Interpret results and identify trends
- 3. Implement custom visuals and R/Python scripts
- Enhance reports with analytics
- 1. Use AI visuals, forecasts, and key influencers
- 2. Apply conditional formatting and custom visuals
- 3. Create paginated reports
- Create reports and dashboards
- 1. Create dashboards and pinned elements
- 2. Design report layout, formatting, and interactivity
- 3. Apply filters, slicers, and drill-through
- 4. Choose appropriate visualizations
|
| Topic 3: Manage and secure Power BI | 15-20% | - Implement security and governance
- 1. Manage permissions and access
- 2. Configure row-level security (RLS) and object-level security
- 3. Apply data sensitivity labels and protection
- Manage workspaces and assets
- 1. Create and configure workspaces
- 2. Manage data refresh and scheduled updates
- 3. Publish, update, and organize reports/datasets
- Deploy and distribute content
- 1. Embed content in applications or websites
- 2. Monitor usage and performance
- 3. Share reports, dashboards, and apps
|
| Topic 4: Model the data | 25-30% | - Create model calculations
- 1. Use DAX: calculated columns, calculated tables, measures
- 2. Implement aggregation and time intelligence
- 3. Use CALCULATE and filter context
- Optimize model performance
- 1. Reduce cardinality and data size
- 2. Use aggregations and composite models
- 3. Optimize relationships and calculations
- Design data models
- 1. Create relationships: cardinality, cross-filter direction, security
- 2. Define tables, columns, and hierarchies
- 3. Implement role-playing dimensions
- 4. Create common date tables
|