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

  • Exam Code: DA-100-Deutsch
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version)
  • Updated: Aug 19, 2026
  • Q & A: 150 Questions and Answers

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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.

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

4. Data Analysis (10-15%):

This section requires your skills in:

  • Caring out advanced analysis: This subject area covers your skills in identifying outliers, using binnings & groupings, conducting Time Series Analysis, and applying AI Insights. The students should also have competence in using decomposition tree visuals to dissect a measure and use Key Influencers for the exploration of dimensional variances.
  • Enhancing reports to expose insights: The candidates should have the expertise in personalizing visuals, applying filters & slicers and conditional formatting. They also need to demonstrate their skills in exploring statistical summary, creating reference lines with Analytics pane, and using Q&A visuals, among others.

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Microsoft DA-100 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prepare the data20%- Transform and load the data
  • 1. Create and transform columns
  • 2. Define relationship cardinality and cross-filter direction
  • 3. Design a star schema
  • 4. Create and transform tables
  • 5. Select appropriate column data types
- Get data from different data sources
  • 1. Identify and connect to a data source
  • 2. Change data source settings
  • 3. Choose an appropriate Power BI data source
  • 4. Select a shared dataset or create a local dataset
  • 5. Select a storage mode
- 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
Topic 2: Visualize the data25%- Create dashboards
  • 1. Set mobile view
  • 2. Configure data alerts
  • 3. Manage tiles on a dashboard
  • 4. Use the Q&A feature
- Enforce accessibility
  • 1. Design accessible reports
  • 2. Configure tab order
  • 3. Use accessibility features
- Create reports
  • 1. Configure conditional formatting
  • 2. Add visualization items to reports
  • 3. Choose an appropriate visualization type
  • 4. Format and configure visualizations
  • 5. Create and manage bookmarks
  • 6. Import a custom visual
  • 7. Apply slicing and filtering
Topic 3: Deploy and maintain deliverables10%- Manage datasets
  • 1. Provide access to datasets
  • 2. Configure a dataset scheduled refresh
  • 3. Configure cross-workspace sharing
  • 4. Configure row-level security group membership
- Create and manage workspaces
  • 1. Assign workspace roles
  • 2. Configure and update a workspace app
  • 3. Create and configure a workspace
Topic 4: Model the data30%- Design a data model
  • 1. Define a relationship's cross-filter direction and security filtering
  • 2. Define the tables
  • 3. Design and implement role-playing dimensions
  • 4. Configure table and column properties
  • 5. Define quick measures
- Optimize model performance
  • 1. Improve performance by choosing optimal data types
  • 2. Improve performance by identifying and removing unnecessary rows and columns
  • 3. Optimize Power Query transformations
- Develop a data model
  • 1. Create calculated columns
  • 2. Implement row-level security roles
  • 3. Create hierarchies
  • 4. Create calculated tables
- Create measures by using DAX
  • 1. Create semi-additive measures
  • 2. Create calculated measures
  • 3. Use DAX logical functions
  • 4. Use DAX aggregation functions
  • 5. Implement Time Intelligence using DAX
Topic 5: Analyze the data15%- Perform advanced analysis
  • 1. Perform What-if analysis
  • 2. Use the Analyze feature
  • 3. Identify outliers
  • 4. Use advanced analytical custom visuals
- Enhance reports for usability and storytelling
  • 1. Configure sync slicers
  • 2. Apply sorting
  • 3. Configure bookmarks
  • 4. Create custom tooltips
  • 5. Group and layer visuals
  • 6. Edit and configure interactions between visuals
  • 7. Configure navigation for a report

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