Microsoft Analyzing and Visualizing Data with Microsoft Excel Exam Certification Details:
| Duration | 120 mins |
| Exam Code | 70-779 |
| Number of Questions | 40-60 |
| Passing Score | 700 / 1000 |
| Books / Training | 20779A: Analyzing Data with Excel |
| Exam Name | Microsoft Certified Solutions Associate (MCSA) - BI Reporting |
| Exam Price | $165 (USD) |
| Schedule Exam | Pearson VUE |
| Sample Questions | Microsoft Analyzing and Visualizing Data with Microsoft Excel Sample Questions |
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70-779 Exam topics
Candidates must know the exam topics before they start of preparation. Because it will really help them in hitting the core. Our 70-779 exam dumps will include the following topics:
- Visualize Data 30-35%
- Consume and Transform Data by Using Microsoft Excel 30-35%
- Model Data 35-40%
Reference: https://www.microsoft.com/en-us/learning/exam-70-779.aspx
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Who should take the 70-779 exam
The Analyzing and Visualizing Data with Microsoft Excel 70-779 Exam certification is an internationally recognized validation that identifies persons who earn it as possessing skilled as an MCSA: BI Reporting. If candidates want significant improvement in career growth needs enhanced knowledge, skills, and talents. The Analyzing and Visualizing Data with Microsoft Excel 70-779 Exam certification provides proof of this advanced knowledge and skill. If a candidate has knowledge of associated technologies and skills that are required to pass Analyzing and Visualizing Data with Microsoft Excel 70-779 Exam then he should take this exam.
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Skills measured
- Visualize Data (30-35%)
- Consume and Transform Data by Using Microsoft Excel (30-35%)
- Model Data (35-40%)
Microsoft 070-779 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Visualize Data | 30-35 | - Create and manage PivotCharts - Create and manage PivotTables - Interact with Power BI |
| Consume and Transform Data by Using Microsoft Excel | 30-35 | - Import from data sources - Perform data transformations - Cleanse data |
| Model Data | 35-40 | - Create hierarchies - Create and optimize data models - Create performance KPIs - Create calculated columns, measures, and tables |
