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SAS, SAP Partner to Boost Big Data Analytics

partner.jpg Now that two competing technology giants have joined forces — SAS, a Cary, N.C.-based developer of analytics software, and enterprise applications provider SAP AG, a German multinational software corporation that makes enterprise software — there's just one question. What’s next?

2014 and Beyond

Karl Schlatzer, senior director of alliances for SAS, told CMSWire that SAP and SAS are evolving their joint platform while “continuing diligence on specific industry and application opportunities and beginning customer validation of the resulting selections.” Expect more announcements throughout 2014, he said.

What’s the partnership all about? In short, the combined platform provides new levels of speed, efficiency and scale for analytic-driven solutions, Schlatzer said.

information management, SAS and SAP Partnership: Analytic-Driven Solutions Get Boost
“Modelcomp” is the SAS Enterprise Miner, data mining software expected to be available on the HANA platform. This shot shows the software comparing two analytics models so that a user can choose the most effective model.

Leaders from both companies also told that the primary goal is to advance in-memory data analysis capabilities for businesses across industries. The partnership leverages the SAP very fast in-memory HANA platform and the analytics capabilities of SAS software. In simplest terms, it incorporates the HANA platform with SAS advanced analytics algorithms.

The partnership was announced at SAP TechEd in Las Vegas late last month.

Walldorf, Germany-based SAP has a large analytics business and just acquired a predictive analytics company, KXEN

However, this is an important move on the company's part, Henry Morris, senior vice president of Worldwide Software and Services and Research at the International Data Corporation (IDC), told It recognizes that to support the needs and requirements of its customers, SAP needs to integrate with the market leaders in adjacent categories, he explained.

“It's not an exaggeration to note that SAP's broad ecosystem is a key contributor to its market success,” Morris said. "And so, even though SAP has become a broader company — moving beyond enterprise apps to analytics, database, mobility — SAP still needs to ensure that market leaders in adjacent categories work well with SAP technology. This is true even though SAP has competing offerings.”

Partnership Goals

At its core, this partnership’s core objective is to “significantly improve overall performance, scalability, and cost-effectiveness of large-scale analytic-driven applications for joint SAS-SAP customers,” Schlatzer said.

SAS-SAP targets specific business areas, Schlatzer added, where the combination of SAS advanced analytics running on the HANA in-memory data and application platform can be expected to yield high-value customer results.

“In so doing, it will provide significant competitive advantage to both SAS and SAP relative to legacy architectures and competitive platforms,” Schlatzer continued. “Executives at both SAP and SAS feel the collaboration can create additional revenue opportunities in both current and new markets.”

information management, SAS and SAP Partnership: Analytic-Driven Solutions Get Boost
“Interactivegraphs” is the SAS Enterprise Miner, showing how users can explore big data using interactive features.

Morris said SAP HANA reduces latency in the data for analysis and provides increased flexibility for users to ask questions of the data. That can eliminate the need for IT to build analytic structures such as pre-aggregated cubes.

One important area of the SAS advanced analytics software involves predictive models. That is “gaining even more importance now, driven by business needs to predict how customers will respond to offers, identifying likely fraud, or predicting when a physical asset is likely to fail,” Morris added.

As data sets increase in size, it’s more efficient, Morris said, to move the model (SAS) to the data (SAP HANA) than the other way around.

“This is important, as increasingly models are being applied in near real-time environments as part of business operations,” Morris said. “This goal is tough to achieve when customers have to export data to SAS and then export the results of the model back to the operational environment. This relationship brings these two areas together in a way that will benefit customers who are both SAP-dependent and SAS-dependent.”


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