Get real DA-100日本語 exam questions for better preparation

Real Microsoft DA-100日本語 practice exam questions for easy pass!

Updated: Jul 24, 2026

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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.

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.

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

Microsoft DA-100日本語 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Analyzing Data with Microsoft Power BI
Exam Number:DA-100
Available Languages:English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Chinese (Traditional), Italian
Exam Format:Multiple choice, Multiple response, Drag and drop, Case study, Build list
Passing Score:700
Exam Price:USD 165
Real Exam Qty:40-60
Certificate Validity Period:Certification valid for one year, renewable
Exam Duration:120 minutes
Related Certifications:Microsoft Certified: Data Analyst Associate
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/

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:

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

4. Data Analysis (10-15%):

This section requires your skills in:

  • Enhancing reports to expose insights: The candidates should have the expertise in personalizing visuals, applying filters & slicers and conditional formatting. They also need to demonstrate their skills in exploring statistical summary, creating reference lines with Analytics pane, and using Q&A visuals, among others.
  • Caring out advanced analysis: This subject area covers your skills in identifying outliers, using binnings & groupings, conducting Time Series Analysis, and applying AI Insights. The students should also have competence in using decomposition tree visuals to dissect a measure and use Key Influencers for the exploration of dimensional variances.

Microsoft DA-100日本語 Exam Syllabus Topics:

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

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