Microsoft 070-779 exam - in .pdf

070-779 pdf
  • Exam Code: 070-779
  • Exam Name: Analyzing and Visualizing Data with Microsoft Excel
  • Updated: Sep 17, 2026
  • Q & A: 118 Questions and Answers
  • PDF Price: $59.99
  • PDF Demo

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  • Exam Code: 070-779
  • Exam Name: Analyzing and Visualizing Data with Microsoft Excel
  • Updated: Sep 17, 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 exam - Testing Engine

070-779 Testing Engine
  • Exam Code: 070-779
  • Exam Name: Analyzing and Visualizing Data with Microsoft Excel
  • Updated: Sep 17, 2026
  • Q & A: 118 Questions and Answers
  • Software Price: $59.99
  • Testing Engine

About Microsoft Analyzing and Visualizing Data with Microsoft Excel : 070-779 Exam Torrent

What is the duration of the 70-779 Exam

  • Number of Questions: 45-60
  • Format: Multiple choices, multiple answers
  • Passing Score: 700/1000
  • Length of Examination: 150 minutes

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How to book the 70-779 Exam

These are following steps for registering the 70-779 exam. Step 1: Visit to Microsoft Exam Registration Step 2: Signup/Login to MICROSOFT account Step 3: Search for MICROSOFT 70-779 Certifications Exam Step 4: Select Date and Center of examination and confirm with payment value of $165

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Analyzing and Visualizing Data with Microsoft Excel 70-779 Exam

Analyzing and Visualizing Data with Microsoft Excel 70-779 Exam which is related to MCSA: BI Reporting Certification. This exam measures and validates the Candidates ability to accomplish the technical tasks like import from data sources, perform data transformations and create calculated columns, measures, and tables. BI Professionals, Data Analysts, and Microsoft Excel Model Data Visualizer usually hold or pursue this certification and you can expect the same job role after completion of this certification.

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Certification Path

The Analyzing and Visualizing Data with Microsoft Excel Certification includes only one 70-779 exam.

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

Microsoft 070-779 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Visualize Data30-35%- Integrate with Power BI
  • 1. Publish Excel data/models to Power BI
    • 2. Refresh and share reports
      - Create and format PivotCharts and visuals
      • 1. Create interactive dashboards
        • 2. Select appropriate chart types
          • 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%- Manage query settings and load
                  • 1. Combine and append queries
                    • 2. Set load options and refresh properties
                      - 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. Split, merge, unpivot, and append columns/tables
                            • 2. Remove duplicates, handle missing values
                              • 3. Apply query parameters and M language
                                • 4. Change data types and format values
                                  Topic 3: Model Data35-40%- Create and manage data models
                                  • 1. Create hierarchies and calculated columns
                                    • 2. Enable and use Power Pivot
                                      • 3. Define tables, columns, and relationships
                                        - Implement DAX calculations
                                        • 1. Work with filter context and row context
                                          • 2. Use basic and advanced DAX functions
                                            • 3. Create measures, KPIs, and calculated tables
                                              - Optimize model performance
                                              • 1. Reduce data size and cardinality
                                                • 2. Set appropriate data types and indexing

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