Collaboration features make it easy to work as a team on ambitious data projects, to share knowledge amongst team members and to onboard new users much faster. You can add documentation, information or comments on all DSS objects.
Every action in the system is versioned and logged through an integrated Git repository. Follow each action from the timeline in the interface, with easy rollback to previous versions.
DSS lets you package a whole workflow as a single deployable and reproducible package. Automate your deployments as part of a larger production strategy. Run all your data scenarios using our REST API.
DSS helps you create clearly defined projects and make sure your data is organized. And with fine grained access rights, your data is available only to the right persons.
For data scientists and developers that need to draft data preparation and modelisation in seconds, that wish to leverage their favorite ML libraries (scikit-learn, R, MLlib, H2O, and so on), and that rely on automating their work in a completely customizable interface.
For data team managers that want easy and complete reporting tools when leading a data project. Simple overviews as well as detailed reports of all activity are available, helping you to see where the project is at, and how it will keep going.
For Data Ops that coordinate development and operations by handling workflow automations, creating predictive web services, monitoring data & model health on a daily basis, and who don’t want to worry about multi-technology platforms.
For Data Analysts that are more efficient in an interactive visual interface where they can point, click, and build or use languages like SQL to data wrangle, model, easily re-run workflows, visualize results, and get up-to-date insights on demand.