Build repeatable workflows that turn AI-generated visualizations into professional, branded outputs.

The Professional DataViz Pipeline

1. Data prep — Clean and structure data with AI assistance
2. Exploration — Use AI to generate 10-20 quick charts exploring different angles
3. Selection — Pick the 3-5 most insightful visualizations
4. Refinement — Polish with brand colors, proper labels, and annotations
5. Narrative — Generate contextual explanations for each chart
6. Presentation — Export in the right format for your audience

Branding Your Charts

"Apply these brand guidelines to the chart: primary color #2563EB, secondary color #7C3AED, font family Inter, background white. Include our company logo position in the top-right corner."

Export Formats

• Presentations — Export as SVG or high-res PNG for slide decks
• Reports — Embed interactive charts or use static images with captions
• Web — Use Claude-generated React components directly in applications
• Print — Export at 300 DPI with CMYK color considerations

Data Storytelling Framework

Structure your data presentations:

1. Setup — "Here's the question we set out to answer"
2. Tension — "Here's what the data revealed (the surprising part)"
3. Resolution — "Here's what this means and what we should do"

Common Visualization Mistakes AI Helps Avoid

• Truncated axes — AI warns when y-axis doesn't start at zero for bar charts
• Wrong chart type — AI suggests alternatives when your choice is misleading
• Color accessibility — AI can apply colorblind-safe palettes automatically
• Overplotting — AI suggests aggregation or sampling for dense scatter plots

Building a Chart Template Library

Save your best AI-generated charts as templates:

• Revenue dashboards
• User growth charts
• A/B test result visualizations
• Survey result summaries
• Funnel analysis charts

Congratulations on completing this course! You now have the skills to turn any dataset into compelling, insight-rich visualizations using AI. 📊