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Course Outline
Data Architecture & Excel Preparation
Topic 1: 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.
- Audience Analysis Matrix: Customizing visuals for C-Suite executives (summary) versus operational teams (granular detail).
- Workshop: Analyzing a "Bad vs. Good" report to understand 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: 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: Crafting titles that summarize the insight rather than just the data.
- Annotation Strategy: Using text boxes, arrows, and highlighting to guide the viewer'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 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.
- 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, or highlighting.
- Accessibility: Designing for color blindness (using ColorBrewer palettes) and ensuring readability in grayscale.
- 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
Introduction to Interactive Visualization (Containerized Tools)
- Tableau vs. R (Shiny/RMarkdown): Determining when to use which tool for static versus interactive reports.
- Connecting to Data: Linking 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: 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: How to cite 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 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
- Familiarity with Excel (including Pivot Tables and VLOOKUP/XLOOKUP basics) is beneficial.
- No prior coding or advanced design experience is required.
Audience:
- Data Analysts, Business Managers, and Strategic Planners.
21 Hours
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