In this post, we will focus our story on how Minerva drastically simplifies and improves the data consumption experience for our users. Specifically, we will showcase how a unified metric layer, which we call the Minerva API, helps us build versatile data consumption experiences tailored to users with a wide range of backgrounds and varying levels of data expertise.
The Minerva API consists of the API web server, a metadata fetcher application, and several clients that integrate with Apache Superset, Tableau, Python, and R. These components serve native NoSQL and SQL metric queries to the downstream applications.
The article discusses the following:
- A metric-centric approach
- Minerva API
- The data consumption experience
Minerva introduced a novel way of thinking about data, not only is it centered around a business- and metric-centric user interface, we also need to adapt traditional BI tools (that mostly talk SQL) to the interface of Minerva API. In some sense, it is akin to fitting a new square peg (Minerva) into an existing round hole ( BI Tools). Very good read for anybody interested in data science!
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