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Microsoft Analyzing Data with Microsoft Power BI - DA-100 real prep

DA-100
  • Exam Code: DA-100
  • Exam Name: Analyzing Data with Microsoft Power BI
  • Updated: Sep 10, 2026
  • Q & A: 150 Questions and Answers
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  • PDF Price: $59.98
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About Microsoft DA-100: Analyzing Data with Microsoft Power BI

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Exam DA-100 Topics Covered

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

  • 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.

  • 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.

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

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:

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

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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.

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Microsoft DA-100 Exam Syllabus Topics:

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

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