⚡ Rill Developer is a tool that makes it effortless to transform your datasets with SQL. These are our release notes for our 0.7 release, still in Tech Preview.
To try out Rill Developer, check out these instructions and let us know over on Discord if you encounter any problems or have ideas about how to improve Rill Developer!
For Rill 0.7, we’ve been hyper-focused on streamlining the workflow, improving the dashboard experience, and improving the stability of the application. These enhancements help you expedite the final mile of turning data into insights.
Dashboards are getting better
We radically cut scope to get an MVP of the dashboard view in 0.6. In this release, the dashboard will get a number of UX improvements that make them feel more screenshot worthy. Most notably, though, is that we’re finding ways to go straight to a dashboard from a data source. Here is a bit more detail:
Faster path to dashboards — You can now go straight from source to dashboard, or model transform to dashboard, with just a click. One way we do this is by continuing to lean into smart assumptions about the dataset and how it maps to measures and dimensions. These can be tuned and refined as you go, but honestly it’s pretty magical to drag and drop a CSV into Rill Developer and begin exploring it in a couple of clicks.
Time grain selector — Data is often collected in very granular units like seconds or milliseconds. bringing data together into time-grain buckets is a useful way to zoom out and look at higher level trends. In this version of Rill Developer we introduce time grains to our dashboard by default to help people quickly switch between different levels of granularity without editing their model transformation.
Stability & polish — Thanks to community feedback, we were able to find a number of bugs and rough edges for the 0.6 release. There’s nothing quite like people proactively reaching out to share the places they are getting stuck and changes they would like to see next! Thanks to these insights we have improved our state management system so you will encounter fewer issues across assets when you are editing your project and get more meaningful feedback at every step.
Other notable improvements
Refining and tuning a dashboard can involve managing model transformations, metric aggregations, and dashboard configs. This release includes three-dot menu interactions for each asset type that are much clearer. It also includes smarter data re-profiling across assets to reduce compute and increase speed to insights.
Clearer interaction menus — We knew that we were shipping a dashboard experience in 0.6 that sparked the imagination when you saw it, but it was not easy to get to. These updates help you navigate the path from data to dashboard with links to upstream assets, creating dashboards, renaming assets, and deleting them. It is amazing what a big difference an icon makes too!
Snappy select * models — The first thing most of us end up doing when we approach a new data set is write select * from tbl, and then begin carving out what we want from it. Since this is so common, we now just pass on the profile from the source to the model directly instead of re-computing it.