cpimhoff

3 ms·

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Show HN: Unifying Warehouse Metrics and Funnel Metrics in Hashboard(hashboard.com)
1 points by cpimhoff 2y ago|0 comments
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by cpimhoff 2y ago
All great advice. All this resonated with the team. 100% on decoupling it from the product. Our customers needed a headless BI solution and we needed a better internal framework, so the stars aligned for this first version being a little co
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by cpimhoff 2y ago
> 1. How does this compare to dbt? If we're already using dbt, why migrate? I actually think dbt and Hashquery work very well alongside one another! dbt can help you normalize, clean, and materialize your data upstream, then Hashque
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by cpimhoff 2y ago
The library itself provides tools for declaring data tables, columns, metrics, and relationships, then performing transformations (eg. queries) on top of them. Reflecting an existing database isn't part of the library, but with the mag
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by cpimhoff 2y ago
> way beyond the capabilities of standard SQL Maybe the more precise language would be "way beyond the _expressive_ capabilities of standard SQL". Ultimately Hashquery compiles into SQL for execution, in that way it's a bi
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by cpimhoff 2y ago
Bit of context here is that Hashquery started as an internal tool and as a way to power our headless BI offering, so it still has a few bits tied to our infrastructure we're working to fully separate. For folks wanting to hack around m
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Show HN: Hashquery, a Python library for defining reusable analysis(hashquery.dev)
67 points by cpimhoff 2y ago|18 comments