Microsoft DA-100日本語 : Analyzing Data with Microsoft Power BI (DA-100日本語版)

  • Exam Code: DA-100日本語
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100日本語版)
  • Updated: Sep 10, 2026
  • Q & A: 150 Questions and Answers

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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:

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

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

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Microsoft DA-100日本語 Exam Syllabus Topics:

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

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