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Microsoft DA-100日本語 valid exam - in .pdf Free Demo

  • Exam Code: DA-100J
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100日本語版)
  • Last Updated: Sep 15, 2026
  • Q & A: 150 Questions and Answers
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Microsoft DA-100日本語 valid exam - Testing Engine PC Screenshot

  • Exam Code: DA-100J
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100日本語版)
  • Last Updated: Sep 15, 2026
  • Q & A: 150 Questions and Answers
  • Uses the World Class DA-100日本語 Testing Engine. Free updates for one year. Real DA-100日本語 exam questions with answers. Install on multiple computers for self-paced, at-your-convenience training.
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About Microsoft DA-100日本語 Valid Exam Questions

Certification Path

After acquiring the Microsoft Certified: Data Analyst Associate certification, you are competent to go further and broaden your expertise in the Microsoft BI platform. Although this certificate is not a direct requirement for other BI-related validations, it will sure help you get started with the higher-level certifications like the Microsoft Certified: Dynamics 365 + Power Platform Solution Architect Expert.

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

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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:

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

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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.
  • 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.
  • 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 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.

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Microsoft DA-100日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prepare the data20-25%- Clean, transform, and load data
- Profile and examine data
- Get data from different sources
Topic 2: Visualize the data20-25%- Apply filters, slicers, and formatting
- Create reports and dashboards
- Enrich reports for usability
Topic 3: Analyze the data10-15%- Perform advanced analysis
- Apply AI visuals and insights
- Identify patterns and trends
Topic 4: Deploy and maintain deliverables10-15%- Configure refresh and security
- Share and distribute content
- Manage workspaces and datasets
Topic 5: Model the data25-30%- Create measures using DAX
- Design and develop data models
- Optimize model performance
- Create calculated tables and columns

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