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What should you know about the Microsoft DA-100 exam before going for it?

The intended candidates for the Microsoft DA-100 exam are Data Analysts. These professionals help the organizations make the most of the value of data assets through the use of Microsoft Power BI. They also collaborate with the major stakeholders across the company to deliver the appropriate insights based on the recognized business prerequisites.

Microsoft DA-100 is an associate-level certification test, and as such, it does not have any official prerequisites. However, Microsoft recommends that the students have a good fundamental knowledge of data processing and data repositories both in Cloud and on-premises. The candidates for the exam should have the relevant skills in building and designing scalable data models, facilitating advanced analytic abilities, and transforming and cleaning data to provide significant business value through understandable data visualizations.

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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.

4. Data Analysis (10-15%):

This section requires your skills in:

  • 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.
  • 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.

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

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