Posted October 11, 2012 by RhoBeta in Analytics

SAS enhances Hadoop power for its High-Performance Analytic Server


The predictive modeling capabilities of SAS High-Performance Analytics Server will now also use Hadoop Distributed File System (HDFS), the popular open source big data infrastructure.The updates also enhance large-scale optimization with select high-performance capabilities in existing servers. SAS augments Hadoop with world-class analytics, plus metadata, security and lineage capabilities, ensuring that Hadoop will be enterprise-ready. SAS Data Management also mitigates the lack of mature tools for developing and managing Hadoop deployments, helping organizations gain value from Hadoop more quickly with fewer resources.

One of the SAS top-level manager said “These latest enhancements, including additional support for Hadoop and HDFS, make it easier to achieve value from Big Data, Hadoop Distributed File System (HDFS) is a fault-tolerant file system that enables high throughput access to application data using commodity, low-cost hardware. With HDFS support, SAS High-Performance Analytic Server can now open up its predictive modeling capabilities to a growing Hadoop ecosystem.”

Currently SAS High-Performance Marketing Optimization offers the ability to:
• Rapidly optimize massive volumes of customer data.
• Quickly solve complex optimization challenges.
• Run optimizations against the entire set of customer data, not just a sample or control group.
• Integrate with SAS High-Performance Analytics – massive amounts of customer data are distributed, optimized and returned in an easy and efficient fashion.

Organizations use SAS analytics to detect fraud, minimize risk, increase response rates for marketing campaigns and curb customer attrition. SAS High-Performance Analytics means finding fraud before claims are paid, evaluating risk more frequently, improving marketing campaigns and reaching valuable customers. Hadoop is a collection of software including: a distributed file system, which can handle large amounts of data storage; map reduce, which processes the data; and common, which is the shared infrastructure that supports the project. Hadoop is already used by some of the largest internet firms in the world, including Amazon Web Services, AOL, Apple, eBay, Facebook, Foursquare, HP, LinkedIn, Netflix, Rackspace, Twitter and Yahoo. Hadoop’s skyrocketing popularity has made the company to pay  attention to the open source Big Data platform.


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