Thanks! With Hubble, we realised that while some companies wanted a separate tool to monitor data quality (e.g. data governance teams in financial integrations) most modern data teams want to test inside their existing code base (e.g. dbt). Also the majority of the company tends to interact with the data through their BI tool and we think that's where adding data quality makes most sense.
For example: flagging a dashboard as out of date, or showing that a report depends on data with failing tests.
There's rich metadata in the transform layer that just isn't getting pulled through to existing reporting/BI/viz tools.
We still have a lot of love for Hubble and data quality monitoring. By connecting dbt and Lightdash, we finally get some of those data monitoring features we always wanted.
Thanks for sharing Rakam, they always stood out for their choice of using dbt as their transform layer, it's really cool.
For example: flagging a dashboard as out of date, or showing that a report depends on data with failing tests.
There's rich metadata in the transform layer that just isn't getting pulled through to existing reporting/BI/viz tools.
We still have a lot of love for Hubble and data quality monitoring. By connecting dbt and Lightdash, we finally get some of those data monitoring features we always wanted.
Thanks for sharing Rakam, they always stood out for their choice of using dbt as their transform layer, it's really cool.