Visual Analytics with Excel
2 DAY COURSE

Data doesn’t speak for itself, but with the right visuals, it can tell a story that drives real decisions. This two-day, hands-on course teaches participants how to unlock the full power of Microsoft Excel for visual data analytics. Through practical exercises and real-world examples, learners will explore foundational visualization principles, advanced charting techniques, interactive dashboards, and even AI-supported analysis.

By the end of the course, participants will know how to design clear, accurate, and engaging visuals; build dynamic dashboards; interpret patterns and insights; and confidently present data-driven stories to stakeholders.

Visual Analytics with Excel Benefits

• Course Benefits

  • Transform raw data into compelling visual narratives using Excel’s full suite of charting, formatting, and dashboarding tools.
  • Learn both the “why” and the “how” by combining strong visualization theory with step-by-step, real-world practice.
  • Build polished dashboards that highlight trends, outliers, and insights for business decision-making.
  • Avoid common visualization mistakes and learn to design visuals that are accurate, intuitive, and trustworthy.
  • Understand how AI fits into Excel workflows and how to structure data for AI-driven analysis and insights.
  • Boost confidence and credibility when presenting charts, dashboards, and data stories to colleagues and leadership. 

  Important Information:

  Prerequisites

  • Basic knowledge of Excel (data entry, formulas) highly recommended but not required.

Visual Analytics with Excel Course Outline

Learning Objectives

Chapter 1. Understanding Visual Data Analytics

• What visual data analytics is
• Why visualization matters
• Types of data
• Principles of effective visualization (clarity, accuracy, simplicity)

Chapter 2. Getting Started with Data in Excel

• Importing and cleaning data
• Structuring data for analysis
• Using Excel tables and named ranges
• Sorting, filtering, and summarizing data

Chapter 3. Exploring Excel’s Charting Tools

• Overview of chart types (column, bar, line, pie, scatter, area, combo)
• When to use each chart type
• Creating basic charts

Chapter 4. Customizing and Formatting Charts

• Editing titles, axes, legends, data labels
• Adjusting colors and styles
• Adding/removing data series
• Using chart templates

Chapter 5. Avoiding Common Pitfalls

• Identifying misleading visuals
• Ensuring data integrity
• Accessibility considerations

Hands-On Activity: Create and customize charts from a sample dataset

Q&A and Discussion

Chapter 6. Advanced Charts and Tools

• PivotTables and PivotCharts
• Dynamic charts with filters and slicers
• Sparklines
• Histograms, box plots, waterfall charts

Chapter 7. Visual Analytics for Decision Making

• Highlighting trends and outliers
• Time-series visuals
• Conditional formatting for visual cues
• Data storytelling techniques

Chapter 8. Dashboards in Excel

• Principles of dashboard design
• Integrating multiple charts and data sources
• Interactive elements (form controls, slicers, hyperlinks)
• Building a simple dashboard

Hands-On Activity: Build your own dashboard

Chapter 9. Sharing and Presenting Visualizations

• Preparing visuals for reports and presentations
• Exporting images/PDFs
• Embedding visuals in PowerPoint and Word
• Using OneDrive and SharePoint for collaboration

Chapter 10. Troubleshooting and Optimization

• Solving common visualization issues
• Working with large datasets
• Maintaining and updating dashboards

Chapter 11. Using AI for Data Analysis

• Benefits and drawbacks of AI
• Structuring data for AI
• Using AI with Excel dashboards

Final Q&A and Participant Presentations