Skip to main content

Rill 0.6 – Introducing radically simple dashboards

Β· 4 min read

⚑ Rill Developer is a tool that makes it effortless to transform your datasets with SQL and create powerful, opinionated dashboards. These are our release notes for the 0.6 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!

Radically simple dashboards​

Ever since our first 0.1 release, we've had countless people in the community ask us if we were planning to add more data visualization and exploration tools on top of our modeling functionality. 0.6 marks our first foray, starting with a simple drill-down dashboard bundled directly into Rill Developer. The dashboard tool enables you to define measures and dimensions on top of models, then provides a fast, powerful, opinionated way to drill down into your dimensions to uncover new trends. We think it still has some of the same reactive magic as our SQL GUI; we like to think of it as a conversation-fast un-dashboard.

Why start here? We know intimately that people basically hate building and maintaining dashboards. Something that seems like it will be so useful ends up becoming unloved over time. We think this is in part because too much responsibility is placed on the analyst to design the dashboard, rather than design (and govern) the metrics, from data source to line chart. And because they're often backed by data warehouses instead of fast OLAP databases, they're cumbersome and cognitively costly to use due to high latency. It doesn't have to be this way! We think we can make something that has the best aspects of both data exploration and presentation.

All of this said, our first version of this dashboard is still alpha-ware. Or to put it bluntly, we radically cut scope to get this product into your hands and start learning about what does and doesn’t work. You can’t really share these with others through a URL quite yet; and its features are pretty bare-bone.

A dashboard has these three components:

  • Line charts β€” Data visualizations of aggregated measures are reactively updated as dimension values are brought in and out of focus using filters.
  • Leaderboards β€” Leaderboards surface the top 7 values for each dimension to quickly identify big segments for each measure.
  • Filters β€” Dynamic filters on measures help you focus on different patterns within the same data set. Our dashboard allows you to focus on different periods of time using the time selector and focus on specific combinations of dimension values using leaderboard filters.

Metrics, designed for people​

Our new Metrics Designer tool complements the dashboard by helping you summarize data models into interpretable metrics for your dashboard. The metrics designer lets you quickly assign a time series, pick drill-down dimensions, and create measures using aggregate SQL expressions. In addition, human readable definitions and labels for metrics and dimensions are connected and discoverable.

Like our dashboard, this is a first pass. We'd love to hear from you about what is and isn't working!

  • Measures and dimensions definitions β€” Definitions that are discoverable and tied to analytics logic logic help dashboard users interpret what they are seeing.
  • Human readable β€” Upstream data work is often done by machines that need to read well-structured strings. However, this is not ideal for people to interpret in dashboards. Rill Developer lets you set a label in place of model column name and format the output to humanized numbers.
  • Automated quick start β€” Automated quick start saves you time by setting all VARCHAR type columns as dimensions and setting COUNT(*) as your first measure.

We don't quite feel we've nailed the user flow of data-to-dashboard, but the point of this release is to get it into your hands. Stay tuned for some user flow refinements!