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Exam Details

Microsoft DA-100 is an associate-level certification exam, which means that irrespective of your current hands-on experience in the subject area, you can still work towards passing this test and obtaining the certificate. All you need is a thorough understanding of the exam topics and diligent preparation.

The DA-100 exam contains 40-60 questions, covering different types, such as case studies, multiple choice, drag and drop, active screen, and build list, among others. This test can be scheduled using Pearson VUE, the official administrator of the Microsoft certification exams. When you are ready to register for this test, you have to pay the fee of $165. This applies to a single sitting for the exam. If you do not get the required passing score that is 720 points, you must pay a new fee to retake the test.

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The contents of DA-100 study materials are all compiled by industry experts based on the examination outlines and industry development trends over the years. It does not overlap with the content of the question banks on the market, and avoids the fatigue caused by repeated exercises. DA-100 exam guide is not simply a patchwork of test questions, but has its own system and levels of hierarchy, which can make users improve effectively. Our study materials contain test papers prepared by examination specialists according to the characteristics and scope of different subjects. Simulate the real Analyzing Data with Microsoft Power BI test environment. After the test is over, the system also gives the total score and correct answer rate.

Certification Opportunities

Upon completion of this single exam and obtaining the certification, the path doesn’t end. The candidates can pursue other Microsoft certificates to expand their competence area. These include the options such as Microsoft Certified: Azure Data Engineer Associate and Microsoft Certified: Azure Data Scientist Associate, to name a few.

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

Microsoft DA-100 Exam Syllabus Topics:

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

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