Yan Holtz, the data viz educator behind data-to-viz.com and the R/Python/D3 graph galleries, joins Mehdi and Alex for a full episode on data visualization in the age of AI.

AI has basically solved the "how do I write the code" problem, which makes the "what makes a good chart" problem matter more than ever - and it's quietly pushing all serious data viz toward JavaScript and D3, even for R and Python people. We get into picking the right chart before writing a line of code, whether dashboards are dying in favor of agents, why D3.js went from the hardest tool to the default, an agent that grades its own charts against the Tufte test, why Shiny and Streamlit may no longer be the right call, the token cost of data work, and whether a chat box is even the right tool to design a visualization.

Subscribe + all links: motherduck.com/explain-analyze

Yan's website : https://www.data-to-viz.com/
Yan's social : https://www.linkedin.com/in/yan-holtz-2477534a/

Chapters
00:00 Welcome + guest intro (Yan Holtz)
01:29 data-to-viz.com: choosing the right chart
07:58 BI is dead, long live BI: dashboards vs agents
17:09 ninejs: interactive ggplot2 charts in Python
20:01 Teaching an AI agent to make beautiful charts
29:20 D3.js: infinite flexibility, now AI-writable
36:24 Shiny: the right tool in the age of AI?
42:02 Token economics: data is token-hungry
46:33 Data visualization in the age of AI
49:37 Outro

#DataViz #DataVisualization #D3js #JavaScript #BI #DuckDB #AI #MotherDuck #ExplainAnalyze