DA-100 Deutsch Study Materials: Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version) & DA-100 Deutsch Certification Training

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

Exam Code: DA-100-Deutsch

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

Updated: Jul 26, 2026

Q & A: 150 Questions and Answers

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About Microsoft Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version) - DA-100 Deutsch exam dumps

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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.

If you are a data analyst striving to get your skills validated in the scope of data assets, transformations, and models, then the Microsoft DA-100 exam is the one that will assist you with this.

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

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Microsoft DA-100 Deutsch Exam Syllabus Topics:

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

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