[buremba]

The main problem is that it's not easy to drill down into a metric in most BI tools because the connection between the dashboard and the source data is usually missing. Looker is one of the first companies that target this specific issue; you transform, model the data, define your metrics before creating your first dashboard. It takes too much effort (also money) to create a (basic?) dashboard because it's not just a "dashboard".

Instead, as data analysts, we usually want to write a bunch of SQL queries, create charts from them and expose the data to our business stakeholders. While they can see the underlying SQL queries of the metrics, it's not easy for them to modify these SQL queries, so they often get lost.

The dashboards have a long tail. For me, you need to get these four steps done beforehand:

1. Move all the company data into a data warehouse and use it as the single source of truth.

2. Model the data with a transformation tool such as dbt and Airflow.

3. Define metrics in one place on top of your data models in a collaborative way. (This layer is new, and we're tapping it at https://metriql.com)

4. Use an interactive BI tool that lets you create dashboards on top of these metrics with drill-down capability.