Use this quick start guide to collect all the information about Microsoft Power BI Data Analyst (PL-300) Certification exam. This study guide provides a list of objectives and resources that will help you prepare for items on the PL-300 Microsoft Power BI Data Analyst exam. The Sample Questions will help you identify the type and difficulty level of the questions and the Practice Exams will make you familiar with the format and environment of an exam. You should refer this guide carefully before attempting your actual Microsoft MCA Data Analyst certification exam.
The Microsoft Power BI Data Analyst certification is mainly targeted to those candidates who want to build their career in Microsoft Power Platform domain. The Microsoft Certified - Power BI Data Analyst Associate exam verifies that the candidate possesses the fundamental knowledge and proven skills in the area of Microsoft MCA Data Analyst.
Microsoft Power BI Data Analyst Exam Summary:
| Exam Name | Microsoft Certified - Power BI Data Analyst Associate |
| Exam Code | PL-300 |
| Exam Price | $165 (USD) |
| Duration | 120 mins |
| Number of Questions | 40-60 |
| Passing Score | 700 / 1000 |
| Books / Training | PL-300T00-A: Design and manage analytics solutions using Power BI |
| Schedule Exam | Pearson VUE |
| Sample Questions | Microsoft Power BI Data Analyst Sample Questions |
| Practice Exam | Microsoft PL-300 Certification Practice Exam |
Microsoft PL-300 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Prepare the Data (25-30%) |
|
| Get or connect to data |
- Identify and connect to data sources or a shared semantic model - Change data source settings, including credentials and privacy levels - Choose between DirectQuery and Import - Create and modify parameters |
| Profile and clean the data |
- Evaluate data, including data statistics and column properties - Resolve inconsistencies, unexpected or null values, and data quality issues - Resolve data import errors |
| Transform and load the data |
- Select appropriate column data types - Create and transform columns - Group and aggregate rows - Pivot, unpivot, and transpose data - Convert semi-structured data to a table - Create fact tables and dimension tables - Identify when to use reference or duplicate queries and the resulting impact - Merge and append queries - Identify and create appropriate keys for relationships - Configure data loading for queries |
Model the Data (25-30%) |
|
| Design and implement a data model |
- Configure table and column properties - Implement role-playing dimensions - Define a relationship's cardinality and cross-filter direction - Create a common date table - Identify use cases for calculated columns and calculated tables |
| Create model calculations by using DAX |
- Create single aggregation measures - Use the CALCULATE function - Implement time intelligence measures - Use basic statistical functions - Create semi-additive measures - Create a measure by using quick measures - Create calculated tables or columns - Create calculation groups |
| Optimize model performance |
- Improve performance by identifying and removing unnecessary rows and columns - Identify poorly performing measures, relationships, and visuals by using Performance Analyzer and DAX query view - Improve performance by reducing granularity |
Visualize and Analyze the Data (25-30%) |
|
| Create reports |
- Select an appropriate visual - Format and configure visuals - Apply and customize a theme - Apply conditional formatting - Apply slicing and filtering - Configure the report page - Choose when to use a paginated report - Create visual calculations by using DAX |
| Enhance reports for usability and storytelling |
- Configure bookmarks - Create custom tooltips - Edit and configure interactions between visuals - Configure navigation for a report - Apply sorting to visuals - Configure Sync Slicers - Group and layer visuals by using the selection pane - Configure drill through navigation - Configure export settings - Design reports for mobile devices - Enable personalized visuals in a report - Design and configure Power BI reports for accessibility - Configure automatic page refresh |
| Identify patterns and trends |
- Use the Analyze feature in Power BI - Use grouping, binning, and clustering - Use AI visuals - Use reference lines, error bars, and forecasting - Detect outliers and anomalies |
Manage and secure Power BI (15-20%) |
|
| Create and manage workspaces and assets |
- Create and configure a workspace - Configure and update a workspace app - Publish, import, or update items in a workspace - Create dashboards - Choose a distribution method - Configure subscriptions and data alerts - Promote or certify Power BI content - Identify when a gateway is required - Configure a semantic model scheduled refresh |
| Secure and govern Power BI items |
- Assign workspace roles - Configure item-level access - Configure access to semantic models - Implement row-level security roles - Configure row-level security group membership - Apply sensitivity labels |
To ensure success in Microsoft MCA Data Analyst certification exam, we recommend authorized training course, practice test and hands-on experience to prepare for Microsoft Power BI Data Analyst (PL-300) exam.