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SAS Makes Triple Play

SAS broadens High-Performance Analytics portfolio, unites formerly siloed marketing applications and adds cloud deployment flexibility.

5 Big Wishes For Big Data Deployments
5 Big Wishes For Big Data Deployments
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SAS unleashed three major announcements at its Global Forum in San Francisco this week, with a wave of new SAS High-Performance Analytics capabilities, a unified SAS Customer Experience marketing suite and added levels of support for public and private cloud deployment of SAS software.

SAS High-Performance Analytics software is designed to take advantage of highly distributed, massively parallel processing (MPP) on memory-intensive X86 servers. It has been a big strategic push for SAS over the last two years as customers demand ever-faster performance.

"The windows of opportunity to compute analytics are getting shorter and shorter," SAS CEO Jim Goodnight recently told InformationWeek in a preview of the Global Forum announcements. "People now want calculations almost in real time with almost everything that we do."

These low-latency demands cut across financial services, retailing, life sciences, oil and gas exploration, manufacturing and other industries. And they're often accompanied by ever-growing volumes of data from new risk, customer behavior, genomic, remote sensor and supply chain measures.

[ Want more on recent SAS data-visualization moves? Read SAS Upgrades Visual Analytics App. ]

SAS previously offered High-Performance versions of industry specific applications such as financial risk analysis and marketing optimization. But with the SAS High-Performance Analytics upgrades announced this week and set for release in June, SAS will bring MPP power to six core products in its portfolio: Statistics, Data Mining, Text Mining, Optimization, Econometrics and Forecasting.

These general-purpose capabilities are applicable to most any industry and were heretofore sold together with standard SAS software. But as part of SAS High-Performance Analytics, the modules can be purchased individually to address the most demanding applications. In this way, customers can step up to high-scale or processing-intensive analysis in an affordable fashion, according to SAS CTO Keith Collins.

"It lowers the entry point and lets people focus on the techniques where there are bottlenecks at scale," Collins told InformationWeek. "That might mean Modeling for customer rewards analysis, Optimization for inventory optimization or Forecasting for retail, as an example."

SAS makes the case that it can address big data variety as well as sheer volume because SAS High-Performance Analytics can now run on Hadoop clusters. Customers need only use SAS' Anyfile Reader utility to map data on Hadoop cluster to SAS.

"We're able to map to and manage the metadata around any file in Hadoop, whether it's JSON, XML, comma-delimited or binary," Collins explained. "If you dump log files into Hadoop, we can also map to those [semi-structured] formats and use them with traditional analytics."

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