Yellowfin

The Yellowfin BI platform has been providing rich data visualisations and insights for more than 20 years. Yellowfin BI includes automated and curated signal detection of data anomalies, flexible and interactive charts and tables and capacity for integration with a wide number of input data feeds.

Yet Yellowfin's unique offering goes beyond the provision of these BI tools, and engages with the social aspect of sharing and understanding data insights. Users can easily pull together charts and tables into formatted reports, which help to tell the story of the data. Reports and signals are presented within the organisation in a social-like feed, with comments, likes and sharing capabilities.

By 2019, Yellowfin had built a mature, popular product, maintained by skilled in-house team, and with thousands of clients all over the world. But it lacked one important fact - a mobile app.

It was recognised very early in the analysis and discovery phase of this project that the Yellowfin mobile app could not simply be the desktop web version shrunk onto a small screen. BI software is regularly used by sophisticated users, mining large data sets for crucial insights when making major business decisions. They lend themselves to large screens with high information density.

The mobile app version instead focused on the social-like feed of reports, signals and discussions about the generated BI artefacts. Advanced configuration and ingestion tools were left out, while elements to read, like and comment on data reports were made available directly from the home screen.

The resulting app almost felt like a new product, or at least a leaner, more accessible, younger sibling of the main desktop system.

We Make Apps was engaged in early 2019 as the mobile app specialists to complete the development of the Yellowfin BI mobile app.

This project involved very close collaboration between our mobile app developers and Yellowfin's own dev team, who were building out the API to support the app in parallel with the app's development. By working so closely, the API was able to be tailored specifically to the needs of the app, which helped produce a lean, performant API and an elegant separation of functionality and presentation.

The success of the original build has led to a fruitful, ongoing relationship, with the addition of new features into the app and a white-labelling project allowing client-specific versions of the app to be published.