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3. Data Visualization (20-25%):
Here the candidates have to show their knowledge of:
- Creating dashboards:This domain will measure the individuals’ skills in managing tiles within a dashboard, setting mobile view, adding dashboard themes, configuring data classification, configuring data alerts, and using Q&A features.
- Creating reports: The examinees must be able to demonstrate their skills in importing custom visuals, configuring and formatting visualization, designing and configuring accessibility, and configuring automatic page refresh. This topic also requires competence in applying filtering and slicing, selecting suitable visualization types, and including visualization items in reports.
- Enriching reports for Usage: This area requires that the test takers develop competence in configuring bookmarks, creating custom tooltips, configuring Sync Slicers, and navigation for reports. It also covers their skills in exporting report data, utilizing selection pane, drill-through & cross filter.
Understanding functional and technical aspects of Exam DA-100: Analyzing Data with Microsoft Power BI Deploy and maintain deliverables
The following will be discussed in MICROSOFT DA-100 exam dumps:
- Promote or certify Power BI content
- Configure and update a workspace app
- Create and configure a workspace
- Identify downstream dataset dependencies
- Apply sensitivity labels to workspace content
- Providing access to datasets
- Assign workspace roles
- Manage datasets
- Create and manage workspaces
- Configure a dataset scheduled refresh
- Configure row-level security group membership
- Publish, import, or update assets in a workspace
- Recommend a development lifecycle strategy
- Configure incremental refresh settings
- Use deployment pipelines
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2. Data Model (25-30%):
The main domains of this section are:
- 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.
- 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.
- 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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Target Audience
The potential candidates for the Microsoft DA-100 exam are Data Analysts. These professionals have the responsibility of enabling organizations to optimize their data asset values through the use of Microsoft Power BI. They also have the job responsibility of building and designing scalable data models, facilitating advanced analytics capacities, and transforming and cleaning data. These duties are aimed to offer significant business values through easy-to-understand data visualization. The Data Analysts also partner with the major stakeholders to deliver significant insights according to the identified business prerequisites.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
Microsoft DA-100日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Model the data | 30% | - Develop a data model
- 1. Create hierarchies
- 2. Implement row-level security roles
- 3. Create calculated tables
- 4. Create calculated columns
- Design a data model
- 1. Define the tables
- 2. Design and implement role-playing dimensions
- 3. Configure table and column properties
- 4. Define a relationship's cross-filter direction and security filtering
- 5. Define quick measures
- Create measures by using DAX
- 1. Create calculated measures
- 2. Implement Time Intelligence using DAX
- 3. Create semi-additive measures
- 4. Use DAX aggregation functions
- 5. Use DAX logical functions
- Optimize model performance
- 1. Optimize Power Query transformations
- 2. Improve performance by choosing optimal data types
- 3. Improve performance by identifying and removing unnecessary rows and columns
|
| Visualize the data | 25% | - Create dashboards
- 1. Configure data alerts
- 2. Use the Q&A feature
- 3. Set mobile view
- 4. Manage tiles on a dashboard
- Enforce accessibility
- 1. Configure tab order
- 2. Design accessible reports
- 3. Use accessibility features
- Create reports
- 1. Choose an appropriate visualization type
- 2. Format and configure visualizations
- 3. Import a custom visual
- 4. Configure conditional formatting
- 5. Apply slicing and filtering
- 6. Add visualization items to reports
- 7. Create and manage bookmarks
|
| Analyze the data | 15% | - Perform advanced analysis
- 1. Identify outliers
- 2. Perform What-if analysis
- 3. Use advanced analytical custom visuals
- 4. Use the Analyze feature
- Enhance reports for usability and storytelling
- 1. Configure bookmarks
- 2. Create custom tooltips
- 3. Configure sync slicers
- 4. Group and layer visuals
- 5. Configure navigation for a report
- 6. Edit and configure interactions between visuals
- 7. Apply sorting
|
| Deploy and maintain deliverables | 10% | - Create and manage workspaces
- 1. Configure and update a workspace app
- 2. Assign workspace roles
- 3. Create and configure a workspace
- 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
|
| Prepare the data | 20% | - Get data from different data sources
- 1. Choose an appropriate Power BI data source
- 2. Select a shared dataset or create a local dataset
- 3. Change data source settings
- 4. Identify and connect to a data source
- 5. Select a storage mode
- Profile the data
- 1. Interpret data distribution and variance
- 2. Identify data anomalies
- 3. Examine data structures
- Transform and load the data
- 1. Define relationship cardinality and cross-filter direction
- 2. Create and transform tables
- 3. Create and transform columns
- 4. Design a star schema
- 5. Select appropriate column data types
- 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
|