Magic Quadrant for Data Science Platforms.Trusted by high-performing data science teams
The Data Science Platform for:
Turbocharge Your Data Science Workflows
A self-service workbench gives you scalable computing, environment management, collaboration, and model deployment — with the same tools, languages, and data sources you already use (R, Python, RStudio, Jupyter, and more).
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Your Data Science Team’s Secret Sauce
A central hub for data science helps you deliver business results faster, scale your team, and increase transparency into in-flight work.
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Empower Data Scientists With a Self-Service Platform
Give data scientists a platform to explore data, run experiments, develop and deploy models — securely and transparently in centralized infrastructure.
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A Sustainable Competitive Advantage
Domino is a central place for data science work across the research lifecycle, from development to deployment. It accelerates innovation, reduces risk and makes it easier to integrate data science into business processes to drive impact.
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How Domino Helps
As a central hub for data science, Domino addresses a variety of common challenges that arise when building data science teams and integrating them into the business.
Self-Service Data Science
Unleash data scientist productivity and free up IT to focus on strategic problems.
Data Science in the Cloud
Front-end to the cloud, automate elastic compute while letting IT control resource usage.
Leverage Open Data Science
Get the agility of open source with the safety of managed environments.
Manage Model Risk
Track and document model development and usage to innovate with lower risk.
Magic Quadrant for Data Science Platforms
Gartner has published its “2017 Magic Quadrant for Data Science Platforms,” and Domino Data Lab is positioned in the ‘Visionaries’ Quadrant based on completeness of vision and ability to execute.
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The Data Science Maturity Model
A framework developed by Domino for data science teams to benchmark themselves and guide investments across people, process, and technology.
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Data Science Platform: What is it? Why is it Important?
As more companies recognize the need for a data science platform. We want to share our vision for the core capabilities a platform should have in order for it to be valuable to data science teams.