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Course Outline

The Architecture of Data & Excel Preparation

Topic 1: The Principles of Captivating Visualization

  • The Data-Ink Ratio: Maximizing the data-to-ink ratio to minimize clutter.
  • The Communication Loop: Balancing information needs with data availability.
  • The Audience Analysis Matrix: Tailoring visuals for C-Suite executives (summary-level insights) versus operational teams (granular details).
  • Workshop: Deconstructing "Bad vs. Good" reports to identify effectiveness factors.

Preparing Datasets for Visualization

  • Data Hygiene: Cleaning, formatting, and structuring data for visualization tools.
  • Identifying Value: Filtering out noise to isolate key performance indicators (KPIs).
  • Excel Prep: Using Power Query (Get & Transform) to clean raw data.
  • Lab 1: Participants prepare a raw, messy CSV dataset for visualization using Excel Power Query.

Excel Visualization: Beyond the Basics

  • Conditional Formatting as Data Viz: Utilizing heat maps, icon sets, and data bars.
  • Sparklines & Slicers: Embedding mini-charts and interactive filters within Excel.
  • The "Forbidden" Charts: Understanding why to avoid pie charts, 3D charts, and double-axis confusion.
  • Lab 2: Building a clean, high-impact Excel dashboard from the dataset prepared in Lab 1.

Writing the Report Narrative (Part 1)

  • Headline-Driven Reporting: Writing titles that summarize the insight, not just the data.
  • Annotation Strategy: Using text boxes, arrows, and highlighting to guide the reader's eye.
  • The "So What?" Factor: Ensuring every chart answers a specific business question.

Design Psychology & Advanced Chart Types

Selecting the Best Chart Types

  • Comparison Charts: Diverging bars, dot plots, and bullet graphs.
  • Distribution Charts: Histograms, box plots, and violin plots.
  • Relationship Charts: Scatter plots with bubble sizing and regression lines.
  • Part-to-Whole: Treemaps and Marimekko charts (as superior alternatives to pie charts).

Layouts for Specific Data Types

  • Time Series: Line charts, area charts, and managing multiple series without clutter.
  • Geographic Patterns: Choropleth maps, heatmaps, and correct geocoding of data.
  • Nested Data: Waffle charts, pyramid charts, and hierarchical lists.
  • Lab 3: Creating three distinct visuals (Time series, Map, and Part-to-Whole) using Excel and/or a containerized R tool.

Design Psychology & Color Coding

  • Color Theory: Using color for categorization, magnitude, and highlighting.
  • Accessibility: Designing for color blindness (using ColorBrewer palettes) and ensuring grayscale readability.
  • Text-Based Visualization: Visualizing sentiment analysis, timelines, and calendars using typography and iconography.
  • GIFs & Infographics: Best practices for converting static data into animated or static infographics.

Interactive Tools & Assembling the Final Report

Intro to Interactive Visualization (Containerized Tools)

  • Tableau vs. R (Shiny/RMarkdown): Determining when to use each tool for static versus interactive reports.
  • Connecting to Data: Linking tools to prepared datasets.
  • Basic Interactivity: Creating filters, dropdowns, and dynamic tooltips.
  • Lab 4: Replicating the Excel dashboard from Day 1 in Tableau/R (simplified) to understand workflow differences.

Assembling the Report (Part 2)

  • The Grid System: Managing alignment, white space, and hierarchy in dashboard design.
  • File Formats: Exporting as high-res PNGs, PDFs for print, or interactive HTML/Excel files.
  • Reference Management: Citing sources within the visual via footnotes, legends, and tooltips.
  • Case Study Analysis: Reviewing real-world examples of "Captivating Reports" in Finance, Marketing, and Healthcare.

Final Capstone Project & Review

  • The Project: Participants receive a new dataset and an audience persona. They must prepare the data, design the layout, and assemble a 1-page "Captivating Report."
  • Peer Review: Group critique focusing on clarity, design, and insight.
  • Closing Remarks: Resources for ongoing learning and a checklist for future reporting workflows.

Requirements

  • Experience with Excel (basic knowledge of Pivot Tables and VLOOKUP/XLOOKUP) is beneficial.
  • No prior coding or advanced design experience is required.

Audience:

  • Data Analysts, Business Managers, Strategic Planners.
 21 Hours

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