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

  • Exam Code: DA-100
  • Exam Name: Analyzing Data with Microsoft Power BI
  • Updated: Aug 03, 2026
  • Q & A: 150 Questions and Answers

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Exam DA-100 Topics Covered

Test DA-100 measures the entrant's skills in 5 different domains:

  • Visualizing the data (20-25%)

    The third domain will test the applicant's know-how of creating reports, dashboards, and enriching reports for usability. This will require the candidate's expertise in adding visualization to reports, choosing a proper visualization style, formatting visualizations, slicing and filtering applications, configuring a report page, building automatic page refresh, etc. The knowledge of R and Python visuals will also be beneficial. Furthermore, it is also essential for the entrant to know how to set dashboard to mobile view, manage tiles, configure data alerts, arrange aspects of the dashboard, and pin live reports. Finally, the applicant needs to enrich the reports by configuring bookmarks, creating custom tooltips, sorting & configuring various Sync Slicers, designing reports for mobile devices, etc.

  • Modeling the data (25-30%)

    This part of the final exam includes designing a data model. Here, the candidate should be able to define and configure tables along with having an idea about various dimensions and relationships. They are also required to be familiar with the concept of cardinality and cross-filter direction. After designing a data model, the applicant should be aware of how to develop it. Therefore, understanding of security filtering, calculated tables, hierarchies, and the implementation of row-level security roles will be beneficial. Furthermore, the entrants' expertise in working with DAX will be tested in this sector. They are required to be capable of using DAX for building complex measures, taking advantage of CALCULATE for manipulating filters using DAX with Time Intelligence, and more. In addition, this portion of DA-100 also involves the optimization of model performance by removing rows and columns, changing data types, managing aggregations, etc. Finally, the entrant should also know how to create semi-additive measures.

  • Preparation of data (20-25%)

    The first domain for DA-100 exam consists of questions that will test the candidate's understanding of data retrieval from various sources. Thus, applicants should be able to identify the data source and connect to it, modify the source settings, select and create various data sets, pick a storage mode, etc. In addition, the examinee should be familiar with the concept of data profiling and have to be able to identify anomalies, study data structures, and examine column properties as well as data statistics. This section also includes cleaning, transforming, and loading data. This means that the entrant must know how to resolve inconsistencies, transform column data types, combine queries, solve data import errors, and more. This topic will also include Microsoft Dataverse, the usage & creation of a PBIDS file, and data flow after the changes are incorporated.

  • Analyzing the data (10-15%)

    In the fourth tested area, the candidate will be asked to enhance reports for exposing insights. This means complying with the need to be well-informed about conditional formatting, slicers, filters, Analytics pane along with a few other concepts. Besides, candidates must be able to add Quick Insights results to reports and use Q&A visuals. Likewise, the exam-taker should be able to know how to execute the advanced analysis. This involves the understanding of outliers, Timer Series analysis, groupings, binning, dimensional variances, decompositions tree visuals, and AI Insights. The exam also requires an understanding of the Play Axis feature and the personalization of visuals.

  • Deployment and maintenance deliverables (10-15%)

    The fifth and final section of DA-100 exam includes managing datasets. The candidate must be able to configure dataset scheduled refresh and row-level security. They are also expected to have an idea about giving access to data sets, incremental refresh settings, and certifying datasets. Moreover, the entrant is required to be well-informed about creating and managing workspaces. They should be able to create and configure workspaces, assign roles in the workspace, and manage the workspace app. Knowing how to import, export, update, and publish workspace assets will be essential. Finally, the candidate needs to know about applying sensitivity labels in workspace contents. The entrant also needs to be capable of identifying downstream data set dependencies and using deployment pipelines.

Ideal Audience and Required Skills

DA-100 is intended for data analysts who use MS Power BI to enhance the value of the data their organization holds. These professionals are responsible for polishing and transforming data, creating expandable data models, and performing data visualizations that can be interpreted and analyzed to withdraw critical information. Data analysts also work alongside other stakeholders of the business to provide relevant data according to their company’s requirements. Thus, a strong prior understanding of both cloud & on-premises data processing and data repositories is also required by those specialists who are going to take test DA-100.

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

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Analyzing Data with Microsoft Power BI Exam Certification Details:

Duration180 mins
Schedule ExamPearson VUE
Passing Score700 / 1000
Number of Questions40-60
Exam Price$165 (USD)
Books / TrainingDA-100T00-A: Analyzing Data with Power BI
Exam NameMicrosoft Certified - Data Analyst Associate
Sample QuestionsAnalyzing Data with Microsoft Power BI Sample Questions
Exam CodeDA-100

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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Microsoft DA-100 Exam Syllabus Topics:

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

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