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

  • Exam Code: DA-100
  • Exam Name: Analyzing Data with Microsoft Power BI
  • Updated: Jul 23, 2026
  • Q&As: 150 Questions and Answers

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Career Opportunities

The professionals with the Microsoft Certified: Data Analyst Associate certification are qualified for a variety of job titles. These include a Junior Data Analyst, an Associate Analyst, an Associate Consultant, a Certified Retail Analyst, a Technology Support Analyst, a Digital Media Analyst, and a Network Analyst. The average salary for these positions is $52,000 per annum.

The Microsoft DA-100 exam (Analyzing Data with Microsoft Power BI) is intended for data analysts and is the only test required to obtain the Microsoft Certified: Data Analyst Associate certificate.

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DA-100 exam dumps

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

The Microsoft DA-100 test is for those individuals who have at least some experience in working with Power Bi although it is not a strict requirement but a recommendation. In addition, the applicant should have some experience in the concepts of scaling data models, data visualizations, data cleaning, and data processing. When it comes to the test details, DA-100 exam is available in English, Chinese (Simplified), Korean, Japanese and will require $165 for registration. The registered candidate can use the Pearson VUE platform for scheduling an exam. In the final test, individuals will experience around 40-60 items that will have to be solved in 3 hours.

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

Microsoft DA-100 Exam Syllabus Topics:

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

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