Best Data Science Software for Red Hat OpenShift

Compare the Top Data Science Software that integrates with Red Hat OpenShift as of September 2026

This a list of Data Science software that integrates with Red Hat OpenShift. Use the filters on the left to add additional filters for products that have integrations with Red Hat OpenShift. View the products that work with Red Hat OpenShift in the table below.

What is Data Science Software for Red Hat OpenShift?

Data science software is a collection of tools and platforms designed to facilitate the analysis, interpretation, and visualization of large datasets, helping data scientists derive insights and build predictive models. These tools support various data science processes, including data cleaning, statistical analysis, machine learning, deep learning, and data visualization. Common features of data science software include data manipulation, algorithm libraries, model training environments, and integration with big data solutions. Data science software is widely used across industries like finance, healthcare, marketing, and technology to improve decision-making, optimize processes, and predict trends. Compare and read user reviews of the best Data Science software for Red Hat OpenShift currently available using the table below. This list is updated regularly.

  • 1
    SAS Visual Statistics
    With SAS Visual Statistics, multiple users can explore data, then interactively create and refine predictive models. Your data scientists and statisticians can act on observations at a granular level using the most appropriate analytical modeling techniques. The result? You'll unearth insights at unprecedented speeds, and find new ways to grow revenue. Easily build and refine models to target specific groups or segments, and run numerous scenarios simultaneously. You can ask more what-if questions to get better results. And put results into action with an automatically generated score code. Empower multiple users to interact with data visually – to add or change variables, remove outliers, etc. Instantly see how changes affect your model's predictive power, and make refinements quickly. Data science teams have the ultimate flexibility of working in their language of choice, so they can use their skills to the fullest. SAS Visual Statistics unites all analytical assets.
  • 2
    SAS Viya
    SAS Viya is a cloud-native data and AI platform that unifies data management, analytics, AI modeling, and governance within a single environment. The platform helps organizations build, validate, deploy, and govern AI models with transparency, fairness, and auditability built into the entire lifecycle. SAS Viya provides seamless access to data across multiple sources and platforms while maintaining governance, lineage tracking, and compliance controls. Businesses can use the platform to accelerate AI model training, improve workflow productivity, and operationalize data-driven decisions at scale. SAS Viya also supports AI agents through the SAS Viya MCP Server, enabling secure integration of AI-powered tools and decision-making processes. The platform is designed to support cloud, hybrid, and on-premises deployments for greater flexibility across enterprise environments.
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