Unify All Analytics Assets for Deployment, Governance & Scalability

Drive better, faster decision making by tapping the full potential of ever-changing open source analytics tools and technologies.

Get the most out of SAS and open source working together. This e-book tells you how

Why choose SAS^® for open integration?

Turn your modeling melting pot into smarter business decisions. SAS enables all thinkers and innovators to extract insights from analytics using their tools of choice. And it provides the standardized deployment rigor that's essential to turning forward-thinking ideas into reality.

Deploy & execute open source models everywhere

Put your models into production with simultaneous access to multiple deployment destinations. Execute analytics however you like – using APIs, in batch, in a private docker, on Azure, etc. The choice is yours.

Govern & orchestrate your analytics ecosystem

Using different tools, frameworks and technologies to develop models fuels innovation and creativity. But it can also mean a level of complexity that makes it difficult to turn analytics into value. SAS supports models in different languages, moving them from sandbox to production in a centralized, governed manner that meets any scalability requirement.

Integrate models into business applications

A model has no value until it becomes a product, tool or solution users can interact with. SAS REST APIs let you easily customize and integrate open source analytics into your business applications so you can realize value quickly.

Look Who's Working Smarter With SAS^® & Open Source Analytics

Organizations across industries are using SAS Viya to reduce the complexity of their open ecosystems and turn analytics into value.

Becoming 'code agnostic' at Cox Automotive

At Cox Automotive, SAS Viya is the glue holding the analytics organization together. With a team that includes people around the world who code in Python, R and SAS, the ability to integrate disparate code, processes and information into one hub that provides consistent delivery of information is particularly impressive.

“We have people programming in multiple interfaces, and they’re using different ways to collaborate on model development," says Shawn Hushman, former Vice President of Decision Sciences for Cox Automotive. "They have different ways they like to publish and show the output and different ways to deploy the models. SAS allows us to stitch it all together.”

“SAS has the ability to bring together the data scientist community like no other solution can.”

Shawn Hushman • Former VP of Decision Sciences • Cox Automotive

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Opening analytics to executives at Cleveland Clinic

At Cleveland Clinic, giving more people access to analytics is a priority, with an aim toward growing analytics maturity across the whole health care system instead of centralizing analytics skills and capabilities in one team. “Our leaders may not know how to build a predictive model, but they need to be able to use data to make better decisions,” says Chris Donovan, Executive Director of Analytics at Cleveland Clinic. “Not everyone is a data scientist. But everyone needs to be able to interact with data at their level.”

This focus on analytics has helped Cleveland Clinic transform from a focus on palliative care to preventive care. And the leaders at Cleveland Clinic want to make data easily available to executives and managers with drag-and-drop capabilities and simple interfaces.

“Analytics is not just a capability that supports your core strategy. It has to be a core strategy of its own.”

Chris Donovan • Executive Director of Analytics • Cleveland Clinic

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Going from prototype to industrial-strength results at Wyndham Destination Network

The analytics team at Wyndham Destination Network uses a combination of open source and enterprise analytics to find innovative solutions to complex problems – from pricing elasticity to resort operations and customer retention.

"One of the main benefits of using both SAS and open source software is that you can let people use the platform they’re most comfortable with," says Jeremy TerBush, Senior Vice President of Analytics at Wyndham Destination Network. "It’s a learning curve for them to completely shift their thinking. To allow everyone to use whatever platform they’re comfortable with is a big productive boost for us. I think we get better answers too. We can collect the best practices and draw from communities of all platforms and have a bigger pool of ideas. It gives us more flexibility within the team to solve the problem in a number of different ways."

“So we’ll do the forecasting with open analytics as an initial prototype. When we’re happy with that first stage, we run it in SAS. For us, it’s easier to create an industrial-strength product in SAS.”

Jeremy TerBush • Senior Vice President of Analytics • Wyndham Destination Network

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Reaping the benefits of industrialized analytical modeling at Wargaming

Wargaming has made billions in the gaming industry, in part by using analytics to help monetize its free-to-play gaming structure. The company initially gravitated toward open source technologies like R, Spark and Python; however, the first models created took three to six months to implement. "We started looking for the solution that could make it scalable for us," says Alex Ryabov, Head of Business Intelligence Data Services at Wargaming.

"In our research," says Ryabov, "SAS was the only viable option." Wargaming data scientists can now create and deploy more models in less time. And as the market grows and Wargaming continues to diversify into other platforms, it will be able to run even more models, retain and acquire more customers, and apply more complex analytics, all within the same analytics platform.