Domino and AWS: The Ideal Platform for Data Science Teams
Data science workloads are ideal for the cloud, because they benefit from burst compute and specialized hardware such as GPUs. Amazon Web Services provides world-class infrastructure and security. Domino adds capabilities specific to data science workflows, letting teams develop and deploy models faster to deliver sustained business value at scale.
Who Does Data Science on AWS with Domino
Monitoring usage of critical datasets and letting business users access powerful data science models for risk modeling.
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Running 10x more experiments on alternative datasets, reducing time to get best trading strategies into the market.
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Better predicting media consumption patterns, improving readers’ experience and reducing manual curation costs.
Accelerating genetic simulations and collaborating on models for optimizing crop yields.
Get the most out of AWS with Domino
Start Real Collaboration
Distributed teams get a central hub where they can share work and build on ideas. Other stakeholders get visibility into the status of projects.
Run More Experiments
Easy access to AWS EC2 machines including GPUs and powerful servers. Run experiments faster and test more ideas to generate better models in less time.
Stay on the Cutting Edge
Domino's open approach lets you choose from all the great open source tools in quantitative research. Easily try new packages without breaking others’ workspaces or production models.
Secure Your Most Valuable IP
Manage access on a project-by-project basis. Version and centrally store all critical assets, end siloed workflows of traditional data science and move work off the desktop.
Deploy to Production
Models can go into production as apps or REST APIs without a costly, time consuming DevOps process, and be supported by AWS high availability infrastructure.
Control Resources and Costs
Administrators get granular visibility into who is using resources and how they are used. Set resource limits, kill run-away jobs, and attribute costs back to users or teams.