Microsoft Analyzing Data with Microsoft Power BI : DA-100

  • Exam Code: DA-100
  • Exam Name: Analyzing Data with Microsoft Power BI
  • Updated: Aug 10, 2026
  • Q & A: 150 Questions and Answers

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About Microsoft Analyzing Data with Microsoft Power BI : DA-100 Exam

More about DA-100 Exam

This test focuses on technical domains such as structuring data, using DAX to create measures, making a data model, acquiring data from numerous sources, and preparing and analyzing data. Also, it checks one’s skills in interpreting reports, revealing data insights, forming dashboards, visualizing data, handling datasets, and lastly, incorporating and maintaining deliverables. The registration fee for DA-100 is $165. The test is available in numerous languages including Japanese, Chinese, Korean, and English. DA-100 can be taken at local physical centers or online under proctored conditions.

Useful Training Courses to Pass DA-100

To help candidates prepare fully and achieve the best possible result in DA-100, Microsoft provides an official four-day instructor-led training named ‘Course DA-100T00-A: Analyzing Data with Power BI’. It has 13 modules, each focusing on a different area that will be assessed in the exam. Along with each section, there are lab exercises that give candidates the opportunity to apply what they learnt during the sessions. After completing this training, the applicants will be able to analyze technical reports, use Power BI to make paginated reports, handle & distribute report assets, and draw up reports for data analysis. Also, they will be able to effectively enhance, polish, transform, and structure data in a way that facilitates the performance of the business.

However, not everyone can participate in this program as there are certain prerequisites. For instance, learners must be acquainted with the concepts of working with data in the cloud, know how to interact with non-relational and relational data in the cloud, be familiar with the virtualization basics, and finally, understand how to carry out data analysis. If a candidate is missing these necessary requirements, then they can obtain them by first going through the ‘Microsoft Azure Data Fundamentals’ training course and then enrolling in this one.

Moreover, note that the vendor also provides six learning paths for self-study. They are completely free and can be a good first step in your revision for the exam. These modules cover different data analysis areas, such as the use of Power BI, visualization, workspaces’ management, and many more.

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Languages: English, Chinese (Simplified), Korean, Japanese, French, German, Spanish

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: prepare the data; model the data; visualize the data; analyze the data; and deploy and maintain deliverables.

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Exam Topics for Exam DA-100: Analyzing Data with Microsoft Power BI

The following will be discussed in MICROSOFT DA-100 practice exams and MICROSOFT DA-100 practice test:

  • Prepare the data
  • Deploy and maintain deliverables
  • Analyze the data
  • Model the data
  • Visualize the data

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100

Microsoft DA-100 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Visualize the data25%- Create reports
  • 1. Add visualization items to reports
  • 2. Apply slicing and filtering
  • 3. Format and configure visualizations
  • 4. Choose an appropriate visualization type
  • 5. Import a custom visual
  • 6. Configure conditional formatting
  • 7. Create and manage bookmarks
- Enforce accessibility
  • 1. Design accessible reports
  • 2. Use accessibility features
  • 3. Configure tab order
- Create dashboards
  • 1. Manage tiles on a dashboard
  • 2. Use the Q&A feature
  • 3. Set mobile view
  • 4. Configure data alerts
Topic 2: Deploy and maintain deliverables10%- Create and manage workspaces
  • 1. Assign workspace roles
  • 2. Configure and update a workspace app
  • 3. Create and configure a workspace
- Manage datasets
  • 1. Configure row-level security group membership
  • 2. Configure a dataset scheduled refresh
  • 3. Configure cross-workspace sharing
  • 4. Provide access to datasets
Topic 3: Prepare the data20%- Profile the data
  • 1. Identify data anomalies
  • 2. Interpret data distribution and variance
  • 3. Examine data structures
- Clean the data
  • 1. Resolve inconsistencies, unexpected or null values, and data quality issues
  • 2. Resolve data import errors
  • 3. Evaluate data, including data statistics and column properties
- Transform and load the data
  • 1. Select appropriate column data types
  • 2. Create and transform columns
  • 3. Define relationship cardinality and cross-filter direction
  • 4. Design a star schema
  • 5. Create and transform tables
- Get data from different data sources
  • 1. Choose an appropriate Power BI data source
  • 2. Identify and connect to a data source
  • 3. Select a shared dataset or create a local dataset
  • 4. Change data source settings
  • 5. Select a storage mode
Topic 4: Analyze the data15%- Perform advanced analysis
  • 1. Use the Analyze feature
  • 2. Use advanced analytical custom visuals
  • 3. Perform What-if analysis
  • 4. Identify outliers
- Enhance reports for usability and storytelling
  • 1. Group and layer visuals
  • 2. Apply sorting
  • 3. Create custom tooltips
  • 4. Configure navigation for a report
  • 5. Configure sync slicers
  • 6. Edit and configure interactions between visuals
  • 7. Configure bookmarks
Topic 5: Model the data30%- Develop a data model
  • 1. Create calculated tables
  • 2. Implement row-level security roles
  • 3. Create hierarchies
  • 4. Create calculated columns
- Create measures by using DAX
  • 1. Create semi-additive measures
  • 2. Use DAX aggregation functions
  • 3. Use DAX logical functions
  • 4. Create calculated measures
  • 5. Implement Time Intelligence using DAX
- Design a data model
  • 1. Define quick measures
  • 2. Define a relationship's cross-filter direction and security filtering
  • 3. Define the tables
  • 4. Configure table and column properties
  • 5. Design and implement role-playing dimensions
- Optimize model performance
  • 1. Optimize Power Query transformations
  • 2. Improve performance by choosing optimal data types
  • 3. Improve performance by identifying and removing unnecessary rows and columns

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