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I think I agree, but I'm not sure where Dave is claiming this is a paradigm shift in data visualization?

One of the key claims is actually that it's based on _old_ established visualization patterns from before BI tools were popular, and therefore results in consistently nice charts. The other key claim is just that it's simple and maintainable.

Sometimes tools & products can be useful as just well executed points in the known design space. You can already do all this with AI, but it's perhaps a little bit less nice and less maintainable.

[I work at dbt/Fivetran]

by mollifier148 hours ago|

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AI can definitely generate whatever you tell it to do, but what to do with that artifact afterwards? If you want it to be reusable it needs to be a well-defined structured protocol/language. What good is a YAML describing a chart if all I can do is to give it back to the agent and say "read this and create a chart from it", the result will be vastly different from the chart you got the first time.

by dgudkov6 hours ago|

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> the result will be vastly different from the chart you got the first time.

AI can generate reusable artifacts including definitions of the data sources, why not? Most BI dashboards are just XML or JSON (or YAML) files and include definitions of data sources (directly or via semantic models). I struggle to see how dbtCharts is different. Yes, your YAML schema is clean and nice, but that's because you're in the early stages :) Once you go through feature bloat, your YAML format will become much more complex.

AI can generate an XML/JSON/YAML definition of a BI report according to a spec and link the data source in whatever form it should be referenced in the file. For instance, here is a skills file for defining data sources (semantic models) in AI-generated Power BI dashboards: https://github.com/microsoft/skills-for-fabric/blob/main/plu...