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.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
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Understanding functional and technical aspects of Exam DA-100: Analyzing Data with Microsoft Power BI Analyze the data
The following will be discussed in MICROSOFT DA-100 exam dumps:
- Enhance reports to expose insights
- Use the Play Axis feature of a visualization
- Personalize visuals
- Use the decomposition tree visual to break down a measure
- Apply AI Insights
- Add a Quick Insights result to a report
- Apply slicers and filters
- Perform advanced analysis
- Identify outliers
- Explore statistical summary
- Use groupings and binnings
- Create reference lines by using Analytics pane
- Conduct Time Series analysis
- Apply conditional formatting
- Use the Q&A visual
- Perform top N analysis
- Use the Key Influencers to explore dimensional variances
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Analyzing Data with Microsoft Power BI Exam Certification Details:
| Number of Questions | 40-60 |
| Exam Price | $165 (USD) |
| Exam Code | DA-100 |
| Books / Training | DA-100T00-A: Analyzing Data with Power BI |
| Exam Name | Microsoft Certified - Data Analyst Associate |
| Passing Score | 700 / 1000 |
| Sample Questions | Analyzing Data with Microsoft Power BI Sample Questions |
| Schedule Exam | Pearson VUE |
| Duration | 180 mins |
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Microsoft DA-100 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Model the data | 25-30% | - Design and develop data models - Create calculated tables and columns - Optimize model performance - Create measures using DAX |
| Topic 2: Deploy and maintain deliverables | 10-15% | - Manage workspaces and datasets - Share and distribute content - Configure refresh and security |
| Topic 3: Analyze the data | 10-15% | - Apply AI visuals and insights - Perform advanced analysis - Identify patterns and trends |
| Topic 4: Prepare the data | 20-25% | - Get data from different sources - Profile and examine data - Clean, transform, and load data |
| Topic 5: Visualize the data | 20-25% | - Enrich reports for usability - Apply filters, slicers, and formatting - Create reports and dashboards |
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