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SAS backs ModelOps as a new way to unleash analytics power

08 Oct 2019
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SAS is refreshing its efforts to help businesses complete the last mile of their analytics to reach goals through new offerings, services, and education.

SAS ModelOps is a new packaged offering that combines SAS Model Manager software and advisory services.

SAS cites IDC statistics that show only 35% of organisations fully deploy analytical models in production, resulting in wasted effort and wasted money.  Because businesses are investing around US$189 billion in analytics in 2019 alone, they should be able to follow their analytics journeys, according to SAS.

“The inability to put analytics into action is one of the biggest challenges across industries,” comments IDC analytics and information management group vice president Dan Vesset.

 “Many organisations adopt a data-driven culture but struggle to actually apply changes that the data suggests. The finish line is to generate real business value from analytics investments, but many businesses are never reaching it, or struggle with the so-called ‘last mile’ of implementing, operationalising and putting analytics to work.”

 “This is because data doesn’t drive an organisation, decisions do,” adds SAS CEO Jim Goodnight.

“We know analytically-driven decisions are better. Analytical models can detect credit-card fraud, manage banking risk, improve marketing accuracy and so much more. SAS knows how to work with companies to finish this last mile and put their analytics, AI and data investments to work.”

SAS ModelOps enables businesses to streamline management, deployment, monitoring, retraining and governance of both SAS and open source analytical models.

It also provides tailored consulting services. Additionally, SAS is introducing a new standalone service, ModelOps Health Check Assessment, intended to help organisations understand how to optimise deployment.

The concept of ModelOps is also gaining traction, but only a few companies are using it. According to SAS, ModelOps involves moving analytical models from the data science lab into IT production, complete with regular updates and deployments as these models are managed, scaled, monitored and retrained as needed.

“SAS believes that to finish the last mile, analytics needs to emulate the applications-development community’s approach to collaboration – DevOps – and adopt practices that will accelerate model creation and deployment,” the company states.

“Because deployment of analytical models is both challenging and valuable, SAS is also introducing a new service, ModelOps Health Check Assessment. Through an on-site workshop, organisations can determine their level of maturity and readiness to successfully deploy and manage analytical models. The assessment also provides recommendations to move the company forward to make better decisions.”

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