The IT Evaluation Guide for the Domino Data Science Platform


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Knowing that models cannot be managed like software or data, Domino was specifically designed with data science workflows in mind while addressing the challenges of all the platform's users across the organization. Data science tools are rapidly evolving and it can be hard to determine what you need and how you compare options. This guide is a distillation of what we've heard from the IT groups in the Fortune 100.

What’s inside:

What is Domino?

Supporting the Data Science Lifecycle

  • Access to Scalable Compute and Data
  • Model Development
  • Model Delivery

Governance, Infrastructure Monitoring, and Guardrails

  • Infrastructure Monitoring, and Guardrails
  • Project and Data Access
  • Software Environment Management
  • Model Authorization


  • Security Functionality
  • Security for Cloud and VPC deployments
  • Employee Security Policies and Procedures
  • Developing Secure Software at Domino

Latest Resources


A Guide To Enterprise MLOps


2020 Gartner Magic Quadrant for Data Science and Machine Learning Platforms


The True Cost of Building a Data Science Platform


Accelerate Adoption of SAS® Data Science Use Cases in the Cloud Using Domino