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Updated: Jul 26, 2026

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Microsoft DA-100日本語 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Analyzing Data with Microsoft Power BI
Exam Number:DA-100
Exam Price:USD 165
Real Exam Qty:40-60
Exam Format:Multiple choice, Multiple response, Drag and drop, Case study, Build list
Certificate Validity Period:Certification valid for one year, renewable
Passing Score:700
Related Certifications:Microsoft Certified: Data Analyst Associate
Exam Duration:120 minutes
Available Languages:English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Chinese (Traditional), Italian
Sample Questions:Microsoft DA-100日本語 Sample Questions
Exam Way:Online (proctored) or Onsite at a Pearson VUE testing center
Pre Condition:Familiarity with data concepts and experience with data analysis
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/data-analyst-associate/

Microsoft DA-100 Practice Test Questions, Microsoft DA-100 Exam Practice Test Questions

The candidates who want to earn the Microsoft Certified: Data Analyst Associate certification must pass one qualifying exam, which is Microsoft DA-100. This test evaluates the ability of the test takers to accomplish specific technical tasks. These include the processes with data, such as analyzing, preparing, maintaining and deploying, visualizing, and modeling.

2. Data Model (25-30%):

The main domains of this section are:

  • Model performance optimization: This module will measure your competence in enhancing cardinality levels through changing data types and summarization. It will also evaluate your skills in eliminating unnecessary columns and rows, creating and managing aggregations, and identifying poorly performing visuals, measures, and relationships.
  • Creation of measures with DAX: The applicants should be able to utilize DAX in building multifaceted measures, use CALCULATE to maneuver filters, and utilize the fundamental statistical functions for enhancing data. This domain also requires their skills in creating semi-additive measures and implementing Time Intelligence with DAX.
  • Data model design: The learners need to have competence in defining tables, role-playing dimensions, quick measures, and cross-filter direction & relationship cardinality. The topic also requires their skills in designing a data model to fulfill the performance prerequisites, creating common data tables, and solving many-to-many relationships.
  • Data model development: This objective requires one’s ability to create hierarchies, calculated tables, and calculated columns. It also covers your skills in establishing Q&A features, implementing row-level security functions, and applying security filtering and cross-filter direction.

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

Microsoft DA-100日本語 Exam Syllabus Topics:

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