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

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

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Online Test Engine: Supports Windows / Mac / Android / iOS, etc., because it is the software based on WEB browser.

Value Pack Total: $209.97  $89.99

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DA-100日本語 exam dumps

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Career Opportunities

The professionals with the Microsoft Certified: Data Analyst Associate certification are qualified for a variety of job titles. These include a Junior Data Analyst, an Associate Analyst, an Associate Consultant, a Certified Retail Analyst, a Technology Support Analyst, a Digital Media Analyst, and a Network Analyst. The average salary for these positions is $52,000 per annum.

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

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Our Analyzing Data with Microsoft Power BI (DA-100日本語版) study question is compiled and verified by the first-rate experts in the industry domestically and they are linked closely with the real exam. Our products' contents cover the entire syllabus of the exam and refer to the past years' exam papers. Our test bank provides all the questions which may appear in the real exam and all the important information about the exam. You can use the practice test software to test whether you have mastered the Analyzing Data with Microsoft Power BI (DA-100日本語版) test practice materials and the function of stimulating the exam to be familiar with the real exam's pace, atmosphere and environment. So our DA-100日本語 exam questions are real-exam-based and convenient for the clients to prepare for the exam.

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.

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Microsoft DA-100日本語 Exam Syllabus Topics:

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

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