Become the hero of your data science team
With Domino’s Enterprise MLOps platform you get a secure, governed, and managed data science platform to drive down risk and cost without locking you into a single vendor or type of infrastructure. At the same time, it eliminates seemingly insurmountable DevOps challenges for data scientists by providing them with self-service access to the infrastructure and tools they need to deliver high-impact data science securely, safely, and at scale.
Scaling data science isn’t easy
There is a reason why organizations need Domino. They are faced with:
- Chaotic tools and infrastructure. Ungoverned tools, data, and infrastructure create operational, regulatory, and security risks. They drive up IT support burdens and costs, and cause friction in the data science lifecycle.
- Silos causing complexity. Data science has grown organically in most organizations, with different teams having different sets of tools, infrastructure, and processes to build models that may not align with IT and security standards. The complexity of supporting these silos drives up IT support burdens and increases risk.
- Complex processes to operationalize models. DevOps requirements and technical debt escalate when each data science team or model has its own stovepipe manual processes.
Estimate Your ROI from Domino
Answer 6 questions and get a high-level estimate of the value Domino can deliver to your organization based on the results of the Forrester Total Economic Impact (TEI) of the Domino Enterprise MLOps platform.
Why do IT teams choose Domino?
We make scaling data science a win-win for your organization. Your code-first data scientists get the tools and infrastructure they need to be most productive. IT avoids an ungoverned, high-risk, high-support cost environment. You have a single location to secure, govern and manage data science tools (e.g, Jupyter, RStudio, SAS, MATLAB, Spark) and infrastructure without having to build, support or future proof it yourself. The business benefits from high ROI data science projects. And you get to be the hero for solving seemingly insurmountable challenges.
- Reduced costs associated with data science tools and infrastructure. No more floods of tickets to support bespoke environments. No more cost escalation from duplicative infrastructure or ungoverned usage in the cloud. Everyone uses the same processes for validation, deployment, and delivery of data science, taking advantage of automation to shorten the time to deployment.
- No more wild west of data science. Increase governance and security of data science infrastructure by testing tools and IDEs before releasing them on Domino. Data access is governed consistently. Compliance activities are streamlined and automated. Platform administration occurs centrally.
- Turbocharged data science research. Easily provision self-serve “sandboxes” with flexible compute and tools including GPUs that can be spun up with a click of a button. You can support distributed compute networks such as Spark, Ray, and Dask to speed through computations. Data scientists become incredibly productive with instant access to appropriately sized infrastructure for their projects.
- Data science aligned with your cloud and modernization initiatives. Domino is a Kubernetes-based, cloud-native platform that can run on-premise or in any cloud. Over time Domino moves with you rather than constraining you with legacy infrastructure.
Domino’s Enterprise MLOps Platform
Domino does more than just manage tools and infrastructure. Domino provides self-service infrastructure in your environment so data science teams can develop and productionize machine learning models faster while IT can govern and manage data science tools (e.g, Jupyter, RStudio, SAS, MATLAB) and infrastructure (e.g. GPUs, Spark, Ray and Dask) in one place. It instills consistent patterns and practices across the entire data science lifecycle, making it easy for IT, data science, and the business to work together to deliver models at scale.
- Data science projects developed and deployed in days not months in a secure environment.
- Automation and workflows eliminating mundane repetitive tasks, freeing resources to spend time on high-value activities.
- Thousands of models in production and monitored without overwhelming DevOps teams.
- Instant reproducibility of any project to satisfy compliance and audit requirements.
- Knowledge management and collaboration to maximize innovation
Data science is unleashed across your organization, scaling to create competitive advantage and business value. That’s what’s happening in over 20% of the Fortune 100 where IT is taking a more proactive role in data science, saving their companies tens of millions in support costs and unlocking research that has generated hundreds of millions of revenue.