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Download Microsoft : DA-100 Deutsch Questions & Answers as PDF & Test Software

Updated: Jun 01, 2026

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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:

  • 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.
  • 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.
  • 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.

Certification Path for Exam DA-100: Analyzing Data with Microsoft Power BI

Analyzing Data with Microsoft Power BI is a fundamental exam and there are no pre-requisites. Successful candidates will get Microsoft Certified: Data Analyst Associate title.

Exam DA-100 Topics Covered

Test DA-100 measures the entrant's skills in 5 different domains:

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

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

The Microsoft DA-100: Analyzing Data with Microsoft Power BI exam measures the capability of the individuals to complete certain technical tasks. These include preparing data, visualizing data, modeling data, analyzing data, and maintaining and deploying deliverables. This is the only test that is required to earn the Microsoft Certified: Data Analyst Associate certification.

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