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Exam DA-100: Analyzing Data with Microsoft Power BI

Data Analysts enable businesses to maximize the value of their data assets by using Microsoft Power BI. As a subject matter expert, Data Analysts are responsible for designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value through easy-to-comprehend data visualizations. Data Analysts also collaborate with key stakeholders across verticals to deliver relevant insights based on identified business requirements.

The Data Analyst should have a fundamental understanding of data repositories and data processing both on-premises and in the cloud.

Part of the requirements for: Microsoft Certified: Data Analyst Associate

Download exam skills outline

Difficulty in Attempting Exam DA-100: Analyzing Data with Microsoft Power BI

However, if you would like to use different source data/tables in the same project, link them together and perform transformations on the data in Power BI as well, then the level of difficulty increases. Learning this will take of course more time. What we believe will also help is to get a general understanding of how data cleansing works and data integration in general. We offer MICROSOFT DA-100 practice exams and MICROSOFT DA-100 practice test for this purpose.

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Compared to other visualization tools we would recommend that Power BI is quite user friendly and is relatively easy to learn. What also contributes to this is that the Power BI desktop version is available for free, resulting in a pretty large user base on the internet, which is beneficial to your learning curve, as in our experience answers to particular questions can be found easily most of the times.

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

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This exam measures your ability to accomplish the following technical tasks: prepare the data; model the data; visualize the data; analyze the data; and deploy and maintain deliverables.

Microsoft DA-100 Exam Syllabus Topics:

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

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