mollifier14

4 ms·

1.
by mollifier14 11d ago
A library is for coding in the classical sense. Declaring in YAML is a very light form of coding I would say, much more accessible to non-engineers. A simple dashboard in YAML is so much more readable to a human than some python code that u
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by mollifier14 11d ago
Yes you can! Chart can have links assigned, either automatically or dynamically. Those links can either take you to drill down pages with the data listed out, or it can dynamically change filter/variable values and change the data disp
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by mollifier14 11d ago
I don't quite understand the YAML hate from some people. I agree that Helm is messy, but it has a lot of coding like things in YAML and then it feel like dependencies just live randomly somewhere. For the most part our YAML files are s
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by mollifier14 12d ago
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 al
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by mollifier14 12d ago
We actually use vega-lite under the hood. vega-lite is vast tool set to build charts with static data. dbt Charts adds a whole layer on top of that, which is dashboards with repeatable SQL queries. Also dbt Charts comes with a lot of opinio
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by mollifier14 12d ago
Sure, machines don't need visualization (although it seems that images are a surprisingly good medium to get context into agents), but humans still do. Mathematicians have plotted functions for a long time now. While the pure truth lie
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by mollifier14 12d ago
I think we're still ways out until companies will blindly trust AI that the data they pulled is correct. If a data team member sees a dashboard or chart, their first questions is "Is the SQL below this chart correct?". The ea
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by mollifier14 12d ago
A beacon of hope between all the vibe coded JS slop charts and dashboards! I love that this creates artifacts that are readable, maintainable and reproduce the same dashboard consistently (deterministically!), just with fresh data.