Last week, SAS Institute Inc. announced enhancements to its SAS Enterprise Miner, SAS Text Miner, and SAS Forecast Server products. 数据挖掘论坛
The new SAS enhancements focus on usability and performance tweaks. SAS Enterprise Miner, for example, boasts new modeling algorithms -- including gradient boosting, partial least squares and support vector machines, which SAS says lets users build more stable and more accurate models. 数据挖掘论坛
SAS also says it has boosted support for unstructured data (from sources such as customer feedback forms, blogs, and call centers) in its SAS Text Miner tool. Users can also import Text Miner results into SAS Enterprise Miner to take advantage of the latter tools' improved data visualization capabilities, SAS officials say.
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SAS Forecast Server now boasts an improved user interface, a more configurable outlier-detection facility, support for more complex filtering, and six new statistics of fit. In addition, SAS Forecast Server offers more than a dozen new project management macros. 数据挖掘交友
The improvements also help shore up SAS' already-impressive predictive analytic story, says Mike Schiff, an analyst with consultancy Current Analysis. Since arch-rival SPSS Inc. announced a revision of its own predictive analytic offering (Clementine) just last month, that's an important consideration, according to Schiff. 数据挖掘交友
"We believe that predictive analytics is such a powerful technology that we are only seeing the tip of the iceberg, as some companies are reluctant to let their competitors know that they are using it as a competitive weapon," he says. "SAS is certainly one of the first names that come to mind when discussing data mining and predictive analytics. It has a strong and loyal installed base that appreciates that to SAS the word 'optimize' is not just a marketing term but rather an objective of its advanced analytics technology."
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The Data Warehousing Institute (TDWI) found that although predictive analytics is an extremely high-value technology -- delivering in many cases head-spinning ROI figures -- it's also relatively underdeployed (see http://www.tdwi.org/News/display.aspx?ID=8699).
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One reason for predictive analytics' relative scarcity -- relative, that is, to its high return on investment -- is its complexity, experts say. 数据挖掘交友
"Predictive analytics is also an arcane set of techniques and technologies that bewilder many business and IT managers," wrote Wayne Eckerson, director of research with TDWI, in a recent report (Predictive Analytics: Extending the Value of Your Data Warehousing). "It stirs together statistics, advanced mathematics, and artificial intelligence and adds a heavy dose of data management to create a potent brew that many would rather not drink!" 数据挖掘交友
Experts say that it isn't unusual for business users to experience a kind of fear and trembling when they're exposed to predictive analytic tools: such tools, for all of their potential, can also be intimidating. 数据挖掘研究院
That's one reason why Schiff is so high on SAS' usability improvements to its Text Miner, Enterprise Miner, and Forecast Server tools. 数据挖掘交友
"Prospects considering predictive analytics and forecasting technology should certainly consider SAS in their evaluations," he says, stressing that SAS, long the market champ in the statistical analysis segment, also fields a highly credible BI platform now, too. 数据挖掘工具
"Users need to be aware that SAS has a fairly rich business intelligence and data integration product portfolio and should consider SAS for both advanced analytics and core BI technology," Schiff indicates. "In addition to its data mining capabilities, SAS can also boast of a comprehensive suite of OLAP and query and reporting products as well as strong data integration and, through its DataFlux subsidiary, data-quality and data-profiling offerings."
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In addition, Schiff concludes, SAS is still growing at a healthy clip in spite of a consolidation wave in the BI and PM segment that's seen high-flying independents such as Business Objects SA, Cognos Inc., and Hyperion Solutions Corp. gobbled up by SAP AG, IBM Corp., and Oracle Corp., respectively.
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