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 BI 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 | 180 mins |
| Number of Questions | 40-60 |
| Passing Score | 700 / 1000 |
| Books / Training | Course PL-300T00: Microsoft Power BI Data Analyst |
| 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 data from data sources |
- Identify and connect to a data source - Change data source settings, including credentials, privacy levels, and data source locations - Select a shared dataset, or create a local dataset - Choose between DirectQuery, Import, and Dual mode - Change the value in a parameter |
| Transform and load the data |
- Select appropriate column data types - Create and transform columns - Transform a query - Design a star schema that contains facts and dimensions - 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 |
| 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 |
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 - Implement row-level security roles |
| Create model calculations by using DAX |
- Create single aggregation measures - Use CALCULATE to manipulate filters - Implement time intelligence measures - Identify implicit measures and replace with explicit measures - Use basic statistical functions - Create semi-additive measures - Create a measure by using quick measures - Create calculated tables |
| Optimize model performance |
- Improve performance by identifying and removing unnecessary rows and columns - Identify poorly performing measures, relationships, and visuals by using Performance Analyzer - Improve performance by choosing optimal data types - Improve performance by summarizing data |
Visualize and Analyze the Data (25-30%) |
|
| Create reports |
- Identify and implement appropriate visualizations - Format and configure visualizations - Use a custom visual - Apply and customize a theme - Configure conditional formatting - Apply slicing and filtering - Configure the report page - Use the Analyze in Excel feature - Choose when to use a paginated report |
| Enhance reports for usability and storytelling |
- Configure bookmarks - Create custom tooltips - Edit and configure interactions between visuals - Configure navigation for a report - Apply sorting - Configure Sync Slicers - Group and layer visuals by using the selection pane - Drill down into data using interactive visuals - Configure export of report content, and perform an export - Design reports for mobile devices |
| Identify patterns and trends |
- Use the Analyze feature in Power BI - Use grouping, binning, and clustering - Incorporate the Q&A feature in a report - Use AI visuals - Use reference lines, error bars, and forecasting - Detect outliers and anomalies - Create and share scorecards and metrics |
Deploy and Maintain Assets (15-20%) |
|
| Create and manage workspaces and assets |
- Create and configure a workspace - Assign workspace roles - Configure and update a workspace app - Publish, import, or update assets in a workspace - Create dashboards - Choose a distribution method - Apply sensitivity labels to workspace content - Configure subscriptions and data alerts - Promote or certify Power BI content - Manage global options for files |
| Manage datasets |
- Identify when a gateway is required - Configure a dataset scheduled refresh - Configure row-level security group membership - Provide access to datasets |
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.