Sunday, 09 August 2020


SAS Viya's new category of cloud analytics assist AI in healthcare

17 June 2020 | News

The upcoming release redefines how analytic decisions are made to improvise the use of artificial intelligence in healthcare by combining the most successful AI and analytics platform with the flexibility and scale of the cloud

image courtesy: freepik

image courtesy: freepik

SAS® Viya® 4, available in late 2020, is engineered to take advantage of the latest cloud technologies. Designed to be delivered and updated continuously, the new architecture helps bring powerful analytics to the medical and healthcare sectors. Because SAS Viya integrates the art of decision making with the science of artificial intelligence (AI) and analytics, organizations will be able to make better decisions, faster. The innovation behind this release underscores SAS’ commitment to helping organizations transform data into intelligence. This transformational release of cloud-native SAS Viya is one outcome of SAS’ $1 billion investment in AI.

“This release marks an aggressive and innovative step for the SAS platform and for our customers,” said COO and CTO Oliver Schabenberger at SAS. “Organizations are asking to fuel their digital transformation with agility, speed, automation, intelligence and continuity. Those are the attributes of SAS Viya 4 – cloud-native advanced analytics and AI for users of all skill levels, turning business intelligence into intelligent business in the cloud.”

“Enterprises are implementing major changes to their data and analytics technology driven by cloud-native architecture,” said Dan Vesset, Group Vice President, Analytics and Information Management at IDC. “SAS Viya enables a flexible and efficient way to execute data and analytics workloads within container- and microservices-enabled architecture. Organizations can decouple the analytics from the environments in which they run to scale-up services quickly and meet decision needs in a much more agile fashion.”

Analytics everywhere, for everyone

SAS is simplifying how AI and machine learning is embedded into decisions. With a reimagined cloud-native architecture and the availability of interactive or programming interfaces, SAS customers will no longer be bound by programming language, data silos or skills. Automated data preparation, machine learning (AutoML) and model deployment improve the productivity of scarce data science resources and expand AI capabilities to those with more widely available skill sets. Results are explained in easy-to-understand terms so all can act in the moment with confidence.

With a renewed focus on APIs, SAS Viya 4 makes it easier for application developers to collaborate with data science teams and respond quickly to changing business needs. These capabilities allow customers to acquire and consume enterprise-scale analytics in the most efficient way; they can consume just the AI services they need.

SAS Viya 4 uses continuous integration, continuous delivery (CI/CD) process that allows customers to choose their release intervals, so they gain access to the latest product innovations the moment they’re ready or can incorporate updates into their own change-management schedules. The container-based architecture, orchestrated by Kubernetes, provides portability across different cloud environments, including Azure, Google, AWS and OpenShift.

Analytics differentiates

Every organization has data, but it’s what they do with the data that matters. Analytically mature organizations know every decision that comes from their models can make a significant impact on the bottom line. SAS Viya 4 simplifies model deployment – helping cross that critical "last mile" of analytics – and offers a central location to monitor and manage the performance of all analytic models.

Organizations also struggle to explain decisions and foster ethical AI adoption. As AI and machine learning become more widespread, SAS Viya 4 centralizes the management of all open source and SAS models, lineage and templates, giving full visibility and control over all modelling activities.


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