DA-100日本語 exam dumps

Microsoft DA-100日本語 Value Package

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  • Exam Code: DA-100日本語
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100日本語版)
  • No. of Questions: 150 Questions and Answers
  • Updated: Aug 07, 2026

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  • Total Questions: 150
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  • Total Questions: 150
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  • Total Questions: 150
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The topics covered in the Microsoft DA-100 Exam include connecting to data sources, transforming and cleaning data, designing data models, creating data visualizations and reports, managing and sharing data, and more. Successfully passing the exam provides candidates with a Microsoft Certification, which showcases their proficiency in the field of data analysis with Microsoft Power BI. Analyzing Data with Microsoft Power BI (DA-100日本語版) certification helps professionals to increase their chances of employment or achieving a promotion within their current organization.

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Microsoft DA-100 (Analyzing Data with Microsoft Power BI) Certification Exam is an excellent certification for data analysts and business intelligence professionals who want to demonstrate their expertise in Power BI. It provides a comprehensive assessment of the candidate's skills and knowledge, and is recognized globally as a standard for excellence in data analysis and visualization.

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

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Useful Books to Pass DA-100

Those preparing for DA-100 test can incorporate the following books from Amazon in their learning process to ensure they pass the exam with high scores:

  • ‘Secrets of DA-100 Analyzing Data with Microsoft Power BI’ by Nikhil J. This Kindle e-book is packed with numerous up-to-date questions & answers for the Microsoft DA-100 exam in order to help students score better. By going through this material, the applicants will assess themselves and will understand how well they can apply all the things they learnt in theory. The e-book has a good track record of helping individuals achieve success in DA-100 test.
  • ‘Exam Ref DA-100 Analyzing Data with Microsoft Power BI 1st Edition’ by Daniil Maslyuk. This is the official book issued by Microsoft for its DA-100 test. The guidance offered in this paperback aims to help candidates acquire all the right skills needed for the exam so they will be able to achieve a high score. The book puts great emphasis on real-world issues and problems so the readers will know what to expect when working in the job role of a data analyst. It provides complete coverage of all the tested objectives, and this content is extremely detailed. The material also includes various ‘what if’ scenarios to encourage critical thinking in students and prepare them for the more challenging exam questions.
  • ‘Learn How to Pass DA-100: Analyzing Data with Microsoft Power BI Exam’. Prepared by Rodrezil Publications, this book compiles advice and tips from candidates who have already passed DA-100 exam and hence offers invaluable first-hand experiences. It also provides the readers with advice from IT experts who know all the ins and outs of the test and know how to deliver this knowledge in an easy-to-understand manner. The goal of this Kindle e-book is to help applicants get over the fear of the exam and pass it on their very first attempt. The material also comes with coupon codes that students can use to take free DA-100 mock tests at Vullam for better preparation and prior self-assessment.
  • ‘Exam DA-100: Data Analyst Associate 25 Test Prep Questions Version II’ by Ger Arevalo. This guide can act as supplementary material when going through hands-on practice, labs, and classes for DA-100. The intent of this book is to reinforce what you learn, and it is also a good last-minute tool that can help students identify their level of readiness. It will help candidates acquire competencies that will be beneficial when working out in the real world.

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Microsoft DA-100日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Deploy and maintain deliverables10%- Create and manage workspaces
  • 1. Configure and update a workspace app
  • 2. Create and configure a workspace
  • 3. Assign workspace roles
- Manage datasets
  • 1. Provide access to datasets
  • 2. Configure cross-workspace sharing
  • 3. Configure a dataset scheduled refresh
  • 4. Configure row-level security group membership
Topic 2: Model the data30%- Develop a data model
  • 1. Create calculated columns
  • 2. Create calculated tables
  • 3. Create hierarchies
  • 4. Implement row-level security roles
- 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. Create calculated measures
  • 2. Use DAX logical functions
  • 3. Use DAX aggregation functions
  • 4. Implement Time Intelligence using DAX
  • 5. Create semi-additive measures
- Design a data model
  • 1. Define quick measures
  • 2. Define a relationship's cross-filter direction and security filtering
  • 3. Configure table and column properties
  • 4. Define the tables
  • 5. Design and implement role-playing dimensions
Topic 3: 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
- Create reports
  • 1. Apply slicing and filtering
  • 2. Add visualization items to reports
  • 3. Configure conditional formatting
  • 4. Create and manage bookmarks
  • 5. Format and configure visualizations
  • 6. Import a custom visual
  • 7. Choose an appropriate visualization type
- Enforce accessibility
  • 1. Use accessibility features
  • 2. Design accessible reports
  • 3. Configure tab order
Topic 4: Prepare the data20%- Profile the data
  • 1. Examine data structures
  • 2. Identify data anomalies
  • 3. Interpret data distribution and variance
- Get data from different data sources
  • 1. Change data source settings
  • 2. Select a shared dataset or create a local dataset
  • 3. Choose an appropriate Power BI data source
  • 4. Identify and connect to a data source
  • 5. Select a storage mode
- Transform and load the data
  • 1. Define relationship cardinality and cross-filter direction
  • 2. Design a star schema
  • 3. Select appropriate column data types
  • 4. Create and transform tables
  • 5. Create and transform columns
- 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
Topic 5: Analyze the data15%- Enhance reports for usability and storytelling
  • 1. Group and layer visuals
  • 2. Configure navigation for a report
  • 3. Create custom tooltips
  • 4. Edit and configure interactions between visuals
  • 5. Apply sorting
  • 6. Configure sync slicers
  • 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

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