SAS and Domino Stop the Problems that Limit Data Science

Silos and Institutional Amnesia

People working with different tools can’t collaborate or share results with the broader team. People start projects from scratch instead of building on past insights. Domino makes it easy for people working with SAS to collaborate and share results with those using other tools and languages. New SAS users can see how past work was done and learn from it.

Opacity of Data Science Projects

Data scientists who need flexibility are setting up their own personal data science environments. Management can’t see the full project portfolio and struggles to demonstrate full value of team’s work. Domino provides SAS users the flexibility to bring in new tools while providing complete visibility of work across the team.

Scalable Infrastructure

Many data scientists are limited by the computer power of their personal machine. They want to take full advantage of SAS capabilities, but can’t use GPUs or large servers to run their workloads. Domino makes it easy and cost effective to deploy SAS using containers, so researchers get the full value of their SAS investment on the hardware they need only at the time they need it.

Works with SAS Licensing

SAS provides usage-based licenses via their SAS Analytics for Containers packaging which works directly in Domino. There's also an option to use seat-based licenses using the SAS Data Science package.


Domino provides an open, language-and-tool agnostic platform that enables data scientists to run experiments and collaborate regardless of language: SAS, Python, R, or others. Data science teams can discuss results, run experiments in parallel, and leverage past work through Domino’s Reproducibility and Collaboration Engine. Lastly, Domino removes DevOps pains by providing one-click access to compute and language environments. SAS is one of the most popular enterprise data science tools. Many companies want to run SAS code and use SAS products through Domino, just as they would use open-source tools through Domino.

One Click to Launch SAS in the Cloud

With a one click, data scientists can choose what type of hardware they want, and Domino will provision the appropriate resources to run SAS scripts or SAS Studio. This speeds up research by letting data scientists run more experiments faster, while saving them time they’d otherwise spend on Dev Ops. Domino works especially well with SAS in containers to easily enable SAS workloads on cloud resources.

How It Works

Domino provides a self-service “workbench” where data scientists can launch interactive tools or run batch scripts. Data scientists get to choose the hardware and tools they want to use, and Domino Reproducibility Engine will automatically track and record the code, data, results, and parameters of every experiment. Domino hosts those artifacts centrally, so they can be shared, searched, discussed, and reused.

Domino supports two ways of running SAS: Interactively, or in batches. Running SAS interactively is ideal for exploratory analysis, SAS Studio provides a web-based GUI for authoring and executing SAS code. Domino lets you spin up SAS Studio environments with one click, on your hardware of choice.

Once your model or analysis becomes more clear, you may want to run it as a batch script. This makes your work more reproducible, and it allows you to more easily execute long-running experiments. Domino lets you execute SAS scripts with one click. In fact, you can execute multiple scripts in parallel to speed up your analysis — Domino will spread out the load across machines, and automatically detect and store your results from each one.

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