Analyzing Data with Microsoft Power BI: DA-100 Exam

"Analyzing Data with Microsoft Power BI", also known as DA-100 exam, is a Microsoft Certification. With the complete collection of questions and answers, BraindumpsPass has assembled to take you through 150 Q&As to your DA-100 Exam preparation. In the DA-100 exam resources, you will cover every field and category in Microsoft Certified: Data Analyst Associate Certification helping to ready you for your successful Microsoft Certification.

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  • Updated on: Aug 24, 2026
  • No. of Questions: 150 Questions & Answers

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  • No. of Questions: 150 Questions & Answers

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Exam DA-100: Analyzing Data with Microsoft Power BI

Data Analysts enable businesses to maximize the value of their data assets by using Microsoft Power BI. As a subject matter expert, Data Analysts are responsible for designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value through easy-to-comprehend data visualizations. Data Analysts also collaborate with key stakeholders across verticals to deliver relevant insights based on identified business requirements.

The Data Analyst should have a fundamental understanding of data repositories and data processing both on-premises and in the cloud.

Part of the requirements for: Microsoft Certified: Data Analyst Associate

Download exam skills outline

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

About Data Analyst Associate and Who It Is Intended for

The Microsoft Certified: Data Analyst Associate is earned by passing DA-100 and is a role-based intermediate-level certification that falls under the Microsoft Power Platform certification hierarchy and authenticates the data analyst's expertise in utilizing Microsoft Power BI in maximizing the businesses' data assets value. The earner of this certificate will be competent to design and develop scalable data models along with cleaning and transformation of data to provide business values through data visualizations. Overall, this certification will be beneficial for data analysts in broadening their technological prowess and the values that they provide for businesses.

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

Requirements

The Microsoft DA-100: Analyzing Data with Microsoft Power BI test does not have any official prerequisite. However, the applicants must understand the content of the exam topics. They also need to have fundamental knowledge of data processing and data repositories in Cloud and on-premises.

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Microsoft DA-100 Exam Syllabus Topics:

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

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