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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.

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How can you prepare for the Microsoft DA-100 exam to succeed?

The candidates can explore various resources to prepare for the Microsoft DA-100 exam. The Microsoft Learning Platform offers many study tools that the learners can use to achieve success in their test. The first step in the preparation process is to go over the detailed exam topics. After that, you can choose your resources carefully. Here are the official recommended materials for the DA-100 test:

  • Free Online Training

    The applicants who prefer self-paced study can explore the learning paths for the Microsoft DA-100 exam. There are six learning paths for this certification test, including Getting Started with Microsoft Data Analytics, Prepare Data for Analysis, Model Data in Power BI, and Visualize Data in Power BI, among others. Each path contains different modules that address particular topics of the exam.

  • Instructor-Led Training

    Microsoft recommends the Analyzing Data with Power BI training course for the candidates taking the DA-100 test. This training focuses on different best practices and methods associated with the technical and business requirements for visualizing, analyzing, and modeling data with Power BI. The individuals will learn how to process and access data from different data sources, including non-relational and relational data.

  • Practice Test

    Microsoft also offers the official practice test for Microsoft DA-100. The exam questions cover all the objectives of the actual test. This means that you will be well prepared for any questions that may be administered in the exam.

  • Books

    The recommended book resource for this test is Exam Ref: DA-100 Analyzing Data with Microsoft Power BI by Daniil Maslyuk. This is a professional-level resource to help the learners optimize their performance in the test and improve their skills. The book can be found on the Microsoft Press Store.

Understanding functional and technical aspects of Exam DA-100: Analyzing Data with Microsoft Power BI Visualize the data

The following will be discussed in MICROSOFT DA-100 exam dumps:

  • Create custom tooltips
  • Configure navigation for a report
  • Design and configure for accessibility
  • Enrich reports for usability
  • Configure bookmarks
  • Add visualization items to reports
  • Use the selection pane
  • Pin a live report page to a dashboard
  • Manage tiles on a dashboard
  • Add a dashboard theme
  • Configure data classification
  • Configure Sync Slicers
  • Configure the report page
  • Use the Q&A feature
  • Create reports
  • Apply slicing and filtering
  • Drilldown into data using interactive visuals
  • Configure data alerts
  • Set mobile view
  • Design reports for mobile devices
  • Apply sorting
  • Create dashboards
  • Format and configure visualizations
  • Edit and configure interactions between visuals
  • Add an R or Python visual
  • Export report data
  • Choose an appropriate visualization type
  • Use drillthrough and cross filter
  • Configure conditional formatting
  • Import a custom visual
  • Configure automatic page refresh

For more info about Exam DA-100: Analyzing Data with Microsoft Power BI

Exam DA-100: Analyzing Data with Microsoft Power BI

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

Microsoft DA-100日本語 Exam Syllabus Topics:

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

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