SherlockML is a cutting edge data science platform that provides the tools and infrastructure for data scientists to easily complete complex analyses and build sophisticated data models, eliminating IT burdens and helping data scientists to work faster and collaborate more effectively.
Designing products that have such a technical and complex core concept is a big challenge. With the effort of a team of brillant software engineers and data scientists, SherlockML was designed to deliver a slick experience to complex (and often painful) tasks that data scientists need to deal with in a daily basis.
The product design system was defined using an atomic design approach, ensuring a consistent and high-quality delivery of the front-end.
The app was designed in Sketch and prototyped in Invision, using Craft.
As in most startups and fast-paced companies, being multi-skill comes very handy. Front-end programming is part of my daily routine, and several assets were done by me directly on code (it was a great opportunity to learn the architecture of ReactJS).
Users can easily interate through projects and with one-click manage their servers and set up environments.
Different views of the file system allow a better organisation of the workspace and the datasets.
Datasets can be rapidly explored and cleaned through Lens, a custom productivity tool that provides in-depth information and advanced visualisations.
Built-in applications take data to a next level, generating insights and amazing visualisations.