3. Data Visualization (20-25%):
Here the candidates have to show their knowledge of:
- 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.
- 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.
- 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.
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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
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
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Microsoft DA-100 Deutsch Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Visualize the data | 25-30% | - Create reports
|
| Model the data | 25-30% | - Create calculated columns and measures
|
| Deploy and maintain deliverables | 10-15% | - Secure and share content
|
| Prepare the data | 20-25% | - Get data from data sources
|
| Analyze the data | 10-15% | - Analyze data patterns
|






