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

Microsoft DA-100 exam
  • Exam Code: DA-100
  • Exam Name: Analyzing Data with Microsoft Power BI
  • Updated: Sep 09, 2026
  • Q & A: 150 Questions and Answers
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About Microsoft DA-100 Exam Questions

Understanding functional and technical aspects of Exam DA-100: Analyzing Data with Microsoft Power BI Visualize the data

The following will be discussed in MICROSOFT DA-100 exam dumps:

  • Create dashboards
  • Drilldown into data using interactive visuals
  • Set mobile view
  • Design and configure for accessibility
  • Configure data classification
  • Export report data
  • Configure automatic page refresh
  • Design reports for mobile devices
  • Use the Q&A feature
  • Manage tiles on a dashboard
  • Choose an appropriate visualization type
  • Configure the report page
  • Use the selection pane
  • Configure conditional formatting
  • Configure bookmarks
  • Configure data alerts
  • Edit and configure interactions between visuals
  • Pin a live report page to a dashboard
  • Import a custom visual
  • Apply sorting
  • Apply slicing and filtering
  • Enrich reports for usability
  • Create custom tooltips
  • Add a dashboard theme
  • Add an R or Python visual
  • Configure navigation for a report
  • Configure Sync Slicers
  • Format and configure visualizations
  • Use drillthrough and cross filter
  • Add visualization items to reports
  • Create reports

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Conclusion: Getting Microsoft Certified Is Challenging But Possible!

The Microsoft Certified: Data Analyst Associate certificate will help secure a career as a data analyst, which will come with it a high paycheck and different career opportunities. However, achieving this certification won’t be easy as one needs to overcome DA-100 (Analyzing Data with Microsoft Power BI) exam. But, with a huge number of study guides available on Amazon and the official MS training course, passing this test is going to be that much easier.

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

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Free Download Pass DA-100 Exam Cram

This certification exam covers a range of skills that the applicants need to develop competency in before sitting for it. These skills are broken into topics and subtopics. Here are the highlights of the subject areas covered in Microsoft DA-100:

  • Model Data: 25-30%

    This topic equips the candidates with the skills and knowledge on how to design the data model. The questions from this subject area will measure their expertise in defining tables, quick measures, role-playing dimensions, cross-filter direction and relationship’s cardinality, and precise level of data granularity. It will also measure competence in the development of data models, creation of measures with the use of DAX, and optimization of model performance.

  • Prepare Data: 20-25%

    This section of the certification exam will evaluate the ability of the candidates to acquire data from various data sources. They also must be able to profile data, which includes identifying data anomalies and examining data structure. It also requires interrogating data statistics and column properties. In addition, the test takers should have competence in cleaning, transforming, and loading the data. This involves resolving inconsistencies, identifying the relevant keys for joins, combining queries, and resolving data import errors.

  • Visualize Data: 20-25%

    Within this domain, the examinees should possess the ability to create reports because the certification test will measure their capability to perform the technical tasks in this area. They will also need to demonstrate their skills in creating dashboards, including setting mobile view, using Q&A features, managing tiles on dashboards, and configuring data classification. The individuals should also be able to improve reports for usability. They will be required to demonstrate their skills in configuring bookmarks, applying to sort, creating custom tooltips, exporting report data, and configuring Sync Slicers.

  • Maintain & Deploy Deliverables: 10-15%

    The applicants for the Microsoft DA-100 exam should also have competence in managing datasets. This involves configuring datasets scheduled refresh, certifying or promoting Power BI content, and providing access to the datasets. The learners also need to have the skills in creating and managing workspaces, creating and configuring workspaces, assigning workspace roles, and using deployment pipelines.

  • Analyze Data: 10-15%

    This part will measure the competence of the students in improving reports to reveal insights. These include competence in applying conditional formatting, personalizing visuals, exploring statistical summary, and using Q&A visuals. It will also evaluate their skills in performing advanced analysis.

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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.

Microsoft DA-100 Exam Syllabus Topics:

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

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