Domino is the system of record and the collaboration hub for data science. By centralizing data science work, Domino makes data science teams more productive, accelerates experimentation, increases collaboration, and lets them deploy work to the business faster.
Accelerate research and eliminate IT bottlenecks
Provision compute environments with one-click, in a cloud or on premise. Domino ships with distributions of the most popular data science tools—Jupyter, RStudio, R, Python, and more-your teams are free to build your own standard environments to share within your organization, as well. Run multiple experiments in parallel to iterate faster. Run multiple experiments in parallel across your hardware or elastically in the cloud to iterate faster.
Drive business impact faster
Data science projects fail without close collaboration with stakeholders. A central hub lets your team expose work to the business more easily, creating a virtuous cycle of feedback and collaboration. One-click ways to publish or deploy models and results ensures your work drives real impact, instead of going unused.
Stop wasting time reinventing the wheel
Domino automatically tracks all data science experiments—code, data, parameters and results—so your team will never lose work and can always reproduce results. This reduces wasted effort and makes it easier to build upon past learnings in the future.
Increased transparency into in-flight work
One central interface lets you check progress on work, see the latest results, get a sense of the most active projects, and leave comments or feedback, without interrupting your team or transacting over email.
Faster onboarding and reduced key-man risk
Standardized compute environments and a canonical place to work lets new hires be productive on their first day. And with work in a central place instead of spread across machines, team members can quickly pick up where others left off, even months later.
More collaboration and shared context
Move the conversation to a central place, out of email. More shared context about ongoing work sparks creativity and new ideas. Code, data sets, results, and discussions are searchable, taggable, and discoverable, so there’s more reuse of existing work and less reinventing the wheel.