Microsoft DA-100 : Analyzing Data with Microsoft Power BI

  • Exam Code: DA-100
  • Exam Name: Analyzing Data with Microsoft Power BI
  • Updated: Jul 16, 2026     Q & A: 150 Questions and Answers

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2. Data Model (25-30%):

The main domains of this section are:

  • Data model design: The learners need to have competence in defining tables, role-playing dimensions, quick measures, and cross-filter direction & relationship cardinality. The topic also requires their skills in designing a data model to fulfill the performance prerequisites, creating common data tables, and solving many-to-many relationships.
  • Model performance optimization: This module will measure your competence in enhancing cardinality levels through changing data types and summarization. It will also evaluate your skills in eliminating unnecessary columns and rows, creating and managing aggregations, and identifying poorly performing visuals, measures, and relationships.
  • Creation of measures with DAX: The applicants should be able to utilize DAX in building multifaceted measures, use CALCULATE to maneuver filters, and utilize the fundamental statistical functions for enhancing data. This domain also requires their skills in creating semi-additive measures and implementing Time Intelligence with DAX.
  • Data model development: This objective requires one’s ability to create hierarchies, calculated tables, and calculated columns. It also covers your skills in establishing Q&A features, implementing row-level security functions, and applying security filtering and cross-filter direction.

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

For more info about Exam DA-100: Analyzing Data with Microsoft Power BI

Exam DA-100: Analyzing Data with Microsoft Power BI

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Certification Opportunities

Upon completion of this single exam and obtaining the certification, the path doesn’t end. The candidates can pursue other Microsoft certificates to expand their competence area. These include the options such as Microsoft Certified: Azure Data Engineer Associate and Microsoft Certified: Azure Data Scientist Associate, to name a few.

Microsoft DA-100 Exam Syllabus Topics:

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

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