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SAS® Analytics for Containers

Easily deploy SAS® Analytics in the cloud.

Quickly build ready-to-run SAS applications that take advantage of flexible, scalable container-enabled environments in the cloud. SAS Analytics for Containers delivers containerized cloud analytics by providing a powerful set of data access, analysis and graphical tools in a containerized package. 

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Run SAS® Analytics in the cloud.

Moving your data processing to a public or private cloud? Now you can easily run SAS Analytics there, too. Putting SAS into a container like Docker gives your data scientists and analytical teams a flexible DevOps environment for working with containerized SAS Analytics in the cloud.

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Simplify and speed up deployment.

Our solution provides the build once, run anywhere flexibility of the container environment, delivering true containerized cloud analytics by making it easier and faster to use SAS Analytics in the cloud. You can access data from nearly any source. Perform sophisticated analyses. Transform raw data into meaningful information. Then present findings using visuals that help decision makers quickly grasp critical issues. And do all this in the cloud with modular containers that simplify deployment.  

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Combine containerized cloud analytics with Hadoop processing power.

Need big data analytics? Add the power of a Hadoop distributed computing environment to the ability to run containerized SAS Analytics in the cloud. Locate SAS Analytics for Containers within or near a Hadoop cluster, and combine it with our in-database technologies for Hadoop – SAS Scoring Accelerator, SAS In-Database Code Accelerator and SAS Data Quality Accelerator. Put your SAS solutions to work on the data stored in Hadoop, and run SAS Analytics inside the Hadoop cluster – taking full advantage of Hadoop’s distributed processing power.

SAS Analytics for Containers containerized cloud analytics data visualizations shown on desktop monitor

Reproduce an experiment at any stage in the research process.

Data scientists working on large, intricate problems can capture an experiment’s state – including data, code, results, package versions, parameters, etc. – at a single point in time. This allows them to quickly reproduce an experiment at any stage in the research process, which saves valuable time.  

SAS Analytics for Containers containerized cloud analytics visual programming environment shown on desktop monitor

Features

  • Container-ready SAS Analytics.
    Provides true containerized cloud analytics – container-ready SAS software that is easy for data scientists to use, easy for IT to deploy.
  • Best-in-class statistical analysis techniques. Includes regressions, decision trees, Bayesian analysis, spatial point pattern analysis, missing data analysis and many more.
  • Web-based programming interface. Includes an intuitive interface, SAS Studio, that lets you access SAS programs, data files and libraries from a web browser.
  • Jupyter Notebook-based access. Lets users directly interact with SAS using the Jupyter interface.
  • Powerful fourth-generation programming languages. Provides highly flexible and extensible 4GLs with easy-to-learn syntax.
  • Prebuilt SAS procedures (SAS PROCs). Handles many common tasks, including data manipulation and management, information storage and retrieval, sophisticated statistical and predictive analysis, and report writing.
  • SAS macro facility. Lets users extend and customize SAS programs by reducing the amount of coding required for common tasks.
  • Hadoop data access. Lets you interact with Hadoop data – for manipulation and modeling – inside the container. Or push processing to the data source, and interact with Hadoop and RDBMSs efficiently and seamlessly.  
Full Features List
System Requirements

Recommended Resources


For more information, read the SAS Analytics for Containers fact sheet.

Download fact sheet


Learn why Gartner named SAS a Leader in the the Magic Quadrant for Data Science Platforms.

Read report


Find out why SAS Analytics for Containers is such a big deal for organizations using containers for applications.

Read blog post
View more resources
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