Microsoft 070-779 dumps - in .pdf

070-779 pdf
  • Exam Code: 070-779
  • Exam Name: Analyzing and Visualizing Data with Microsoft Excel
  • Updated: Aug 27, 2026
  • Q & A: 118 Questions and Answers
  • PDF Price: $59.99
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  • Exam Code: 070-779
  • Exam Name: Analyzing and Visualizing Data with Microsoft Excel
  • Updated: Aug 27, 2026
  • Q & A: 118 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $119.98  $79.99
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Microsoft 070-779 dumps - Testing Engine

070-779 Testing Engine
  • Exam Code: 070-779
  • Exam Name: Analyzing and Visualizing Data with Microsoft Excel
  • Updated: Aug 27, 2026
  • Q & A: 118 Questions and Answers
  • Software Price: $59.99
  • Testing Engine

About Microsoft Analyzing and Visualizing Data with Microsoft Excel Dumps Question

For more info visit:

Microsoft 70-779 Exam Reference

Reference: https://www.microsoft.com/en-us/learning/exam-70-779.aspx

Microsoft Analyzing and Visualizing Data with Microsoft Excel Exam Certification Details:

Number of Questions40-60
Exam Price$165 (USD)
Exam Code70-779
Duration120 mins
Sample QuestionsMicrosoft Analyzing and Visualizing Data with Microsoft Excel Sample Questions
Books / Training20779A: Analyzing Data with Excel
Schedule ExamPearson VUE
Passing Score700 / 1000
Exam NameMicrosoft Certified Solutions Associate (MCSA) - BI Reporting

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070-779 exam dumps

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:

  • Consume and Transform Data by Using Microsoft Excel 30-35%
  • Model Data 35-40%
  • Visualize Data 30-35%

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Skills measured

  • Consume and Transform Data by Using Microsoft Excel (30-35%)
  • Model Data (35-40%)
  • Visualize Data (30-35%)

Microsoft 070-779 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Visualize Data30-35%- Integrate with Power BI
  • 1. Refresh and share reports
    • 2. Publish Excel data/models to Power BI
      - Create and format PivotCharts and visuals
      • 1. Select appropriate chart types
        • 2. Create interactive dashboards
          • 3. Format charts and apply conditional formatting
            - Create and manage PivotTables
            • 1. Design and configure PivotTables
              • 2. Apply filters, slicers, and timelines
                • 3. Group and sort data
                  Topic 2: Consume and Transform Data by Using Microsoft Excel30-35%- Import data from multiple sources
                  • 1. Import from text, CSV, XML, JSON, web, databases
                    • 2. Use Power Query to connect to data
                      - Clean and transform data
                      • 1. Change data types and format values
                        • 2. Apply query parameters and M language
                          • 3. Remove duplicates, handle missing values
                            • 4. Split, merge, unpivot, and append columns/tables
                              - Manage query settings and load
                              • 1. Combine and append queries
                                • 2. Set load options and refresh properties
                                  Topic 3: Model Data35-40%- Optimize model performance
                                  • 1. Reduce data size and cardinality
                                    • 2. Set appropriate data types and indexing
                                      - Create and manage data models
                                      • 1. Enable and use Power Pivot
                                        • 2. Create hierarchies and calculated columns
                                          • 3. Define tables, columns, and relationships
                                            - Implement DAX calculations
                                            • 1. Use basic and advanced DAX functions
                                              • 2. Work with filter context and row context
                                                • 3. Create measures, KPIs, and calculated tables

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