Microsoft DA-100 : Analyzing Data with Microsoft Power BI

DA-100 real exams

Exam Code: DA-100

Exam Name: Analyzing Data with Microsoft Power BI

Updated: Nov 07, 2026

Q & A: 150 Questions and Answers

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Analyzing Data with Microsoft Power BI Exam Certification Details:

Exam CodeDA-100
Duration180 mins
Books / TrainingDA-100T00-A: Analyzing Data with Power BI
Exam Price$165 (USD)
Exam NameMicrosoft Certified - Data Analyst Associate
Number of Questions40-60
Sample QuestionsAnalyzing Data with Microsoft Power BI Sample Questions
Passing Score700 / 1000
Schedule ExamPearson VUE

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How can you prepare for the Microsoft DA-100 exam to succeed?

The candidates can explore various resources to prepare for the Microsoft DA-100 exam. The Microsoft Learning Platform offers many study tools that the learners can use to achieve success in their test. The first step in the preparation process is to go over the detailed exam topics. After that, you can choose your resources carefully. Here are the official recommended materials for the DA-100 test:

  • Free Online Training

    The applicants who prefer self-paced study can explore the learning paths for the Microsoft DA-100 exam. There are six learning paths for this certification test, including Getting Started with Microsoft Data Analytics, Prepare Data for Analysis, Model Data in Power BI, and Visualize Data in Power BI, among others. Each path contains different modules that address particular topics of the exam.

  • Instructor-Led Training

    Microsoft recommends the Analyzing Data with Power BI training course for the candidates taking the DA-100 test. This training focuses on different best practices and methods associated with the technical and business requirements for visualizing, analyzing, and modeling data with Power BI. The individuals will learn how to process and access data from different data sources, including non-relational and relational data.

  • Books

    The recommended book resource for this test is Exam Ref: DA-100 Analyzing Data with Microsoft Power BI by Daniil Maslyuk. This is a professional-level resource to help the learners optimize their performance in the test and improve their skills. The book can be found on the Microsoft Press Store.

  • Practice Test

    Microsoft also offers the official practice test for Microsoft DA-100. The exam questions cover all the objectives of the actual test. This means that you will be well prepared for any questions that may be administered in the exam.

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

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.
  • 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.
  • 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.

Microsoft DA-100 Exam Syllabus Topics:

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

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