Why Choose Domino for Data Science?


Whether you’re a data scientist, a software developer or a technical operations manager, you will benefit from Domino. It’s a platform that centralizes your work, makes it reproducible and reusable, and speeds up your team’s analytical workflows. It also lets you share and collaborate with other data scientists.

Domino provides a data science workbench that lets data scientists run hundreds of machine learning experiments in parallel, enabling them to create and share reproducible models. It also provides elastically-scaled compute and a governed environment, which fosters collaboration. It also makes it easy to publish and share results.

Domino centralizes model deployment and management processes, and provides users with access to distributed frameworks, NVIDIA GPUs and self-serve, Kubernetes-based compute clusters. This makes it easy to spread jobs across machines and eliminates guessing compute needs. In addition, the platform can host models as REST API endpoints. The resulting models can then be exported to other infrastructure. This simplifies model deployment and scales processes across multiple teams. It also helps ease the learning curve and increase platform adoption.

Domino centralizes code execution and provides access control, enabling collaboration and sharing. It also detects and handles conflicts between code and data, and sends notifications of changes. It makes it easy to monitor resources and reschedule jobs automatically. Unlike other platforms, Domino provides a single, unified interface for managing all your data science workflows. Its tools make it easy to collaborate, share, and experiment 10x faster.

Domino also enables collaboration and makes it easy to manage environments, allowing teams to work across software platforms, languages, and teams. It also provides tools to deploy and scale models, publish results, and publish models as Docker images. The platform’s easy-to-use tools make it easy to experiment with the right data. It also provides an underlying, scalable compute environment, so you don’t have to worry about data bottlenecks or inefficiencies.

Domino centralizes workflows, and lets you build lightweight self-service web forms and apps. It also integrates with Shiny, Dash, and Flask, allowing you to create apps with ease. The Domino team is also available to answer questions and provide support.

Domino’s Enterprise MLOps Platform is a cloud-based platform for automating elastic compute, designed to handle data science workloads. It allows users to easily manage and scale their compute clusters, publish models, and schedule automatic recurring jobs. It also provides IT with monitoring capabilities and tools to help them understand resource usage. The platform also helps improve collaboration and accelerates modern analytical workflows.

Domino centralizes all of your production model management processes, and makes it easy to scale your teams’ production workloads. It also lets you expose your models to business processes. You can deploy models as Docker images and use them in CI/CD pipelines, or host them as REST API endpoints. It also helps you manage high availability and security, and gives you access to NVIDIA GPUs. It also provides a governed environment, letting you experiment with the right data.