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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 reduce clutter.
- The Communication Loop: Balancing information needs with data availability.
- The Audience Analysis Matrix: Tailoring visuals for C-Suite executives (summaries) versus Operational teams (granular details).
- Workshop: Deconstructing a "Bad vs. Good" report and identifying why the latter is effective.
Preparing Datasets for Visualization
- Data Hygiene: Cleaning, formatting, and structuring data for visualization tools.
- Identifying Value: Filtering noise and isolating key performance indicators (KPIs).
- Excel Prep: Using Power Query (Get & Transform) to clean raw data.
- Lab 1: Participants take a raw, messy CSV dataset and prepare it for visualization using Excel Power Query.
Excel Visualization: Beyond the Basics
- Conditional Formatting as Data Viz: Using heat maps, icon sets, and data bars.
- Sparklines & Slicers: Embedding mini-charts and interactive filters in 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 Lab 1 dataset.
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 eye.
- The "So What?" Factor: Ensuring every chart answers a 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 (replacing the pie chart).
Layouts for Specific Data Types
- Time Series: Line charts, area charts, and handling multiple series without clutter.
- Geographic Patterns: Choropleth maps, heatmaps, and correct geocoding.
- 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): When to use each tool for static vs. interactive reports.
- Connecting to Data: Linking the tools to your 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: 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 (footnotes, legends, tooltips).
- Case Study Analysis: Reviewing real-world examples of "Captivating Reports" in Finance, Marketing, and Healthcare.
Final Capstone Project & Review
- The Project: Participants are given 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 (Pivot Tables, VLOOKUP/XLOOKUP basics) is beneficial.
- No prior coding or advanced design experience is required.
Audience:
- Data Analysts, Business Managers, Strategic Planners.
21 Hours
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