Microsoft DA-100 Deutsch valid 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: Sep 27, 2026
  • Q&As: 150 Questions and Answers

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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:

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

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DA-100 Deutsch exam dumps

Exam Topics

Microsoft expects that the successful candidates get the passing score of 720 points on a scale of 100-1000. This mark is achievable if you put your mind to it. To succeed, you must understand the Microsoft DA-100 exam topics that are as follows:

1. Data Preparation (20-25%):

This part includes the following areas:

  • Collecting data from various data sources: The candidates must be able to connect and identify data sources, alternate data source settings, and choose storage mode and shared datasets, or build local datasets. They also need the capacity to select the relevant query type, utilize parameters, Microsoft Dataverse, create or use PBIDS files, and data flow.
  • Data profile: The test takers should have competence in interrogating data statistics and column properties as well as identifying data anomalies and evaluating data structures.
  • Cleaning, loading, & transforming data: This subject area requires that the students understand how to combine queries, utilize user-friendly value substitutions, solve data import errors, transform and measure column data types, and configure the data loading. It also covers their skills in applying data shape transformations for table structures and user-friendly conventional naming for queries and columns. The individuals should also have the expertise in leveraging Advanced Editor or modifying Power Query M-code.

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

Career Opportunities

The professionals with the Microsoft Certified: Data Analyst Associate certification are qualified for a variety of job titles. These include a Junior Data Analyst, an Associate Analyst, an Associate Consultant, a Certified Retail Analyst, a Technology Support Analyst, a Digital Media Analyst, and a Network Analyst. The average salary for these positions is $52,000 per annum.

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Microsoft DA-100 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Visualize the data25-30%- Create reports
  • 1. Use visuals such as charts, maps, and tables
    • 2. Design interactive reports in Power BI Desktop
      - Enhance reports
      • 1. Use bookmarks and navigation elements
        • 2. Apply filters, slicers, and drill-through
          Model the data25-30%- Design data models
          • 1. Design star and snowflake schemas
            • 2. Create relationships between tables
              - Create calculated columns and measures
              • 1. Use DAX for calculations
                • 2. Optimize model performance
                  Prepare the data20-25%- Get data from data sources
                  • 1. Select appropriate storage modes (Import, DirectQuery, Composite)
                    • 2. Connect to data sources (files, databases, cloud services)
                      - Clean and transform data
                      • 1. Use Power Query Editor for data shaping
                        • 2. Handle missing, duplicate, and inconsistent data
                          Deploy and maintain deliverables10-15%- Secure and share content
                          • 1. Implement row-level security (RLS)
                            • 2. Share dashboards with users and groups
                              - Manage workspaces and datasets
                              • 1. Publish reports to Power BI Service
                                • 2. Configure dataset refresh schedules
                                  Analyze the data10-15%- Analyze data patterns
                                  • 1. Identify trends and outliers
                                    • 2. Use AI visuals and quick insights
                                      - Perform advanced analytics
                                      • 1. Use DAX time intelligence functions
                                        • 2. Apply statistical measures in reports

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