Microsoft DA-100 Questions & Answers - in .pdf
- Total Q&A: 150
- Update: Sep 14, 2026
- Price: $59.99
- Vendor: Microsoft
- Exam Code: DA-100
- Exam Name: Analyzing Data with Microsoft Power BI
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- Complete Microsoft Recommended Syllabus.
- Free DA-100 PDF Demo Available.
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- Exact Microsoft DA-100 Exam Questions with Correct Answers, verified by Experts with years of Experience in IT Field.
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Microsoft DA-100 Q&A - Testing Engine
- Total Q&A: 150
- Update: Sep 14, 2026
- Price: $59.99
- Vendor: Microsoft
- Exam Code: DA-100
- Exam Name: Analyzing Data with Microsoft Power BI
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Useful Training Courses to Pass DA-100
To help candidates prepare fully and achieve the best possible result in DA-100, Microsoft provides an official four-day instructor-led training named ‘Course DA-100T00-A: Analyzing Data with Power BI’. It has 13 modules, each focusing on a different area that will be assessed in the exam. Along with each section, there are lab exercises that give candidates the opportunity to apply what they learnt during the sessions. After completing this training, the applicants will be able to analyze technical reports, use Power BI to make paginated reports, handle & distribute report assets, and draw up reports for data analysis. Also, they will be able to effectively enhance, polish, transform, and structure data in a way that facilitates the performance of the business.
However, not everyone can participate in this program as there are certain prerequisites. For instance, learners must be acquainted with the concepts of working with data in the cloud, know how to interact with non-relational and relational data in the cloud, be familiar with the virtualization basics, and finally, understand how to carry out data analysis. If a candidate is missing these necessary requirements, then they can obtain them by first going through the ‘Microsoft Azure Data Fundamentals’ training course and then enrolling in this one.
Moreover, note that the vendor also provides six learning paths for self-study. They are completely free and can be a good first step in your revision for the exam. These modules cover different data analysis areas, such as the use of Power BI, visualization, workspaces’ management, and many more.
Target Audience
The potential candidates for the Microsoft DA-100 exam are Data Analysts. These professionals have the responsibility of enabling organizations to optimize their data asset values through the use of Microsoft Power BI. They also have the job responsibility of building and designing scalable data models, facilitating advanced analytics capacities, and transforming and cleaning data. These duties are aimed to offer significant business values through easy-to-understand data visualization. The Data Analysts also partner with the major stakeholders to deliver significant insights according to the identified business prerequisites.
For more info about Exam DA-100: Analyzing Data with Microsoft Power BI
Exam DA-100: Analyzing Data with Microsoft Power BI
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
Microsoft DA-100 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|
| Prepare the data | 20% | - Get data from different data sources
- 1. Identify and connect to a data source
- 2. Select a shared dataset or create a local dataset
- 3. Change data source settings
- 4. Choose an appropriate Power BI data source
- 5. Select a storage mode
- Transform and load the data
- 1. Select appropriate column data types
- 2. Create and transform columns
- 3. Create and transform tables
- 4. Define relationship cardinality and cross-filter direction
- 5. Design a star schema
- 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. Interpret data distribution and variance
- 2. Identify data anomalies
- 3. Examine data structures
|
| Model the data | 30% | - 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
- Design a data model
- 1. Design and implement role-playing dimensions
- 2. Define quick measures
- 3. Define the tables
- 4. Configure table and column properties
- 5. Define a relationship's cross-filter direction and security filtering
- Develop a data model
- 1. Create hierarchies
- 2. Create calculated columns
- 3. Implement row-level security roles
- 4. Create calculated tables
- Create measures by using DAX
- 1. Create calculated measures
- 2. Use DAX logical functions
- 3. Use DAX aggregation functions
- 4. Implement Time Intelligence using DAX
- 5. Create semi-additive measures
|
| Visualize the data | 25% | - Enforce accessibility
- 1. Configure tab order
- 2. Design accessible reports
- 3. Use accessibility features
- Create reports
- 1. Create and manage bookmarks
- 2. Format and configure visualizations
- 3. Import a custom visual
- 4. Apply slicing and filtering
- 5. Add visualization items to reports
- 6. Configure conditional formatting
- 7. Choose an appropriate visualization type
- Create dashboards
- 1. Set mobile view
- 2. Configure data alerts
- 3. Manage tiles on a dashboard
- 4. Use the Q&A feature
|
| Analyze the data | 15% | - Perform advanced analysis
- 1. Use the Analyze feature
- 2. Identify outliers
- 3. Use advanced analytical custom visuals
- 4. Perform What-if analysis
- Enhance reports for usability and storytelling
- 1. Create custom tooltips
- 2. Group and layer visuals
- 3. Apply sorting
- 4. Configure navigation for a report
- 5. Edit and configure interactions between visuals
- 6. Configure sync slicers
- 7. Configure bookmarks
|
| Deploy and maintain deliverables | 10% | - Create and manage workspaces
- 1. Create and configure a workspace
- 2. Assign workspace roles
- 3. Configure and update a workspace app
- Manage datasets
- 1. Configure row-level security group membership
- 2. Configure cross-workspace sharing
- 3. Provide access to datasets
- 4. Configure a dataset scheduled refresh
|
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