Microsoft DA-100-Deutsch exam dumps : 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: Jul 20, 2026     Q & A: 150 Questions and Answers

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

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

  • Apply conditional formatting
  • Use the Play Axis feature of a visualization
  • Use the decomposition tree visual to break down a measure
  • Create reference lines by using Analytics pane
  • Use the Q&A visual
  • Perform advanced analysis
  • Explore statistical summary
  • Identify outliers
  • Apply slicers and filters
  • Use the Key Influencers to explore dimensional variances
  • Perform top N analysis
  • Add a Quick Insights result to a report
  • Conduct Time Series analysis
  • Personalize visuals
  • Enhance reports to expose insights
  • Apply AI Insights
  • Use groupings and binnings

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

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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.

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Microsoft DA-100 Deutsch Exam Syllabus Topics:

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

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