SAS Analytics Pro – now available for on-site or containerized cloud-native deployment – providing your entry point into SAS Viya

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As its thousands of users know, SAS Analytics Pro consists of three core elements of the SAS system: Base SAS®, SAS/GRAPH® and SAS/STAT®. It provides the fundamental capabilities of data handling, data visualization, and statistical analysis either through coding or through the SAS Studio interface. For many years, SAS Analytics Pro has been deployed on-site as the entry-level workhorse to the SAS system.

Now, SAS Analytics Pro includes a new option for containerized cloud-native deployment. This makes SAS Analytics Pro a perfect entry point into SAS Viya. In addition, the containerized option comes with the full selection of SAS/ACCESS engines making it even easier to work with data from virtually any source. For organizations considering the move to the cloud, or those already there, SAS Analytics Pro provides an exciting new option for cloud deployment.

What is SAS Analytics Pro?

SAS Analytics Pro is an easy-to-use, yet powerful package for accessing, manipulating, analyzing and presenting information. It lets organizations improve productivity with all the tools and methods needed for desktop data analysis – in one package.

  • Organizations can get analysis, reporting and easy-to-understand visualizations from one vendor. Rather than having to piece together niche software packages from different vendors, this consolidated portfolio reduces the cost of licensing, maintenance, training and support – while ensuring that consistent information is available across your enterprise.
  • Innovative statistical techniques are provided with procedures constantly being updated to reflect the latest advances in methodology. Organizations around the world rely on SAS to provide accurate answers to data questions, along with unsurpassed technical support.
  • SAS software integrates into virtually any computing environment, unifying your computing efforts to get a single view of your data, and freeing analysts to focus on analysis rather than data issues.
  • Easily build analytical-style graphs, maps and charts with virtually any style of output that is needed, so you can deliver analytic results where they’re needed most

Why data scientists should care about cloud and containers?

With the new containerized cloud-native deployment option for SAS Analytics Pro, this raises the question of why data scientists should care about cloud and containers? This question was addressed in a SAS Users blog post by SAS R&D director Brent Laster.

This post characterizes a container as a “self-contained environment with all the programs, configuration, initial data, and other supporting pieces to run applications.” The nice thing for data scientists is that this environment can be treated as a stand-alone unit, to turn on and run at any time – sort of a “portable machine.” It provides a complete virtual system configured to run your targeted application.

Using popular container runtime environments (e.g., Docker), containers can be an efficient way for individual users to deploy and manage software applications. This is especially useful for applications like SAS Analytics Pro, which participates in SAS Viya’s continuous delivery approach, releasing updates on a regular basis.

For large, IT-managed environments, containers can call for something like a “data center” to simplify deployment and management of dynamic workloads. The most prominent one today is Kubernetes, which automates key needs around containers including deployment, scaling, scheduling, healing, and monitoring – so the data scientist doesn’t have to.

The combination of containers and cloud environments provides an evolutionary jump in the infrastructure and runtime environments where data scientists run their applications. And this gives them a similar jump in being able to provide the business value their customers demand. Coupling this new containerized and cloud-native SAS Analytics Pro with Kubernetes orchestration can provide the automatic optimization of resources and the automatic management of workloads that your organization needs to be competitive.

Note that existing customers can continue programming in SAS in a small footprint environment while availing themselves of the SAS container-based continuous delivery process. And if you aren’t already a SAS customer, cloud deployment gives you one more good reason to start letting SAS Analytics Pro deliver value to your organization.

Learn more

Website: SAS® Analytics Pro
Training: SAS® Global Certification Program

On-Premises Documentation:

Cloud-Native Documentation:

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About Author

Mike Gilliland

Product Marketing Manager

Michael Gilliland is a longtime business forecasting practitioner and currently Product Marketing Manager for SAS Forecasting. He is on the Board of Directors of the International Institute of Forecasters, and is Associate Editor of their practitioner journal Foresight: The International Journal of Applied Forecasting. Mike is author of The Business Forecasting Deal (Wiley, 2010) and editor of the free e-book Forecasting with SAS: Special Collection (SAS Press, 2020). He is principal editor of Business Forecasting: Practical Problems and Solutions (Wiley, 2015) and Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning (Wiley, 2021). In 2017 Mike receive the Institute of Business Forecasting's Lifetime Achievement Award. In 2021 his paper "FVA: A Reality Check on Forecasting Practices" was inducted into the Foresight Hall of Fame. Mike initiated The Business Forecasting Deal blog in 2009 to help expose the seamy underbelly of forecasting practice, and to provide practical solutions to its most vexing problems.

6 Comments

  1. I wish IML is in the Analytics Pro package. IML is in free On-Demand Academics version where I learn it. IML does compuations like R and Python but in SAS program.

  2. That is a reasonable way at looking at this. We consider this APro offering a stepping stone to full-blown, CAS-inclusive Viya. For those not in need of CAS, but looking to modernize to a containerized deployment which is fueled by the Viya continuous delivery release approach, this could be just the ticket.

  3. Thanks, so is this kind of "Viya without CAS"? If I don't have the need for CAS for big data / in memory, but I want to have a modern environment for BASE SAS, SAS/STAT, and also other packages (SAS/QC, IML, ETS ... ) is this the best path to consider for a future SAS environment? My IT folks that maintain our SAS 9 BI environment think the future is Viya/CAS or nothing, but maybe I should encourage them to explore this option?

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