DA-100 Deutsch Practice Materials are highly similar to the real exam. DA-100 Deutsch Study Guide covers all knowledge points for the customers. DA-100 Deutsch Preparation Questions have been adapted and compiled carefully to ensure they are suitable for all people.

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

DA-100 Deutsch Exam Questions
  • Exam Code: DA-100-Deutsch
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version)
  • Updated: Jul 29, 2026
  • Q & A: 150 Questions and Answers
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About Microsoft DA-100 Deutsch Exam Guide

What is the Microsoft DA-100 exam?

The Microsoft DA-100 exam is available in English, Japanese, Simplified Chinese, and Korean. The learners can expect 40-60 questions in the delivery of the test with the time allowance of 180 minutes. Depending on where they are taking the exam, it is available as a proctored option or at any Pearson VUE testing center. The candidates can register for this certification exam with Pearson VUE and pay the fee of $165 to schedule it. This price is established for the individuals from the United States. If you sit for the test in another country, you should check the actual price on the official website.

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

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

  • Identify query performance issues
  • Choose an appropriate query type
  • Apply data shape transformations to table structures
  • Interrogate column properties
  • Apply user-friendly naming conventions to columns and queries
  • Use or create a PBIDS file
  • Change data source settings
  • Interrogate data statistics
  • Identify and connect to a data source
  • Use parameters
  • Resolve inconsistencies, unexpected or null values, and data quality issues
  • Use or create a data flow
  • Resolve data import errors
  • Identify and create appropriate keys for joins
  • Select a shared dataset or create a local dataset
  • Evaluate and transform column data types
  • Configure data loading
  • Leverage Advanced Editor to modify Power Query M code
  • Combine queries
  • Identify data anomalies
  • Apply user-friendly value replacements
  • Use Microsoft Dataverse
  • Select a storage mode
  • Examine data structures

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DA-100 Deutsch exam dumps

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.

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

Highly similar to the real exam

Now, our DA-100 Deutsch practice materials are become more and more professional. We can predicate almost half real exam questions every year. Although there are small adaptions to the questions of our DA-100 Deutsch study guide, the answers are still the same. So we strongly advise you to memorize our study materials carefully especially the difficult questions of our DA-100 Deutsch preparation questions. You must cultivate the good habit of reviewing the difficult parts, which directly influences your passing rate. What is more, our experts never stop researching the questions of the real DA-100 Deutsch exam. If you have time to know more about our study materials, you can compare our study materials with the annual real questions of the DA-100 Deutsch exam. In addition, we will try our best to improve our hit rates. You will not wait for long to witness our great progress. It is worth fighting for your promising future.

Microsoft DA-100 Deutsch Exam Syllabus Topics:

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

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