Microsoft DA-100 Deutsch Exam : Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version)

Microsoft DA-100 Deutsch exam
  • Exam Code: DA-100-Deutsch
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version)
  • Updated: Aug 17, 2026
  • Q & A: 150 Questions and Answers
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What is the cost of Exam DA-100: Analyzing Data with Microsoft Power BI

The cost of Exam DA-100: Analyzing Data with Microsoft Power BI is $165.

  • Passing Score: 70%
  • Format: Multiple choices, multiple answers
  • Number of Questions: 40
  • Length of Examination: 90 minutes

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

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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.

  • 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.

  • 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.

  • 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.

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5. Deliverables Deployment and Maintenance (10-15%):

The topics for this part are the following:

  • Datasets management: In the framework of this subtopic, the applicants will be evaluated based on their skills in configuring incremental refresh settings, dataset scheduled refresh, and group membership for row-level security. It will also measure their skills in providing access to the datasets and certifying or promoting Power BI content.
  • Workspaces creation and management: The test takers must have competence in assigning workspace roles, using deployment pipeline, updating and configuring workspace apps, and applying sensitivity labels for workspace content. It also requires their skills in importing, updating, and publishing assets in workspaces, as well as recommending the development lifecycle strategy.

Microsoft DA-100 Deutsch Exam Syllabus Topics:

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

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