Banks have long struggled to make sense of the oceans of data they produce. They can buy tools to help mine, analyze and structure really big amounts of data, but until now, these products have not been very user-friendly, limiting their appeal.
One of the latest data discovery products, announced Thursday by SAS Institute, promises to let non-IT folks in banks do complex big data modeling from their own computers.
Data discovery products typically rely on an in-memory middleware layer that can pull and temporarily store massive amounts of data quickly.
With its SAS Visual Analytics product, "we can have the modelers [at banks] who used to build one model a day, because it took so long, build a model every 15 minutes," says James Goodnight, the Cary, N.C., company's chief executive.
The hope, says Goodnight, is that analysts will spend more time analyzing business lines and less time gathering and modeling data.
About five U.S. banks have signed up for the product so far, Goodnight says.
"SAS is now in the market with a strong self-service in-memory tool that continues the development of more user-friendly data mining," says James Kobielus, a senior analyst at Forrester.
Visual Analytics relies on an in-memory software layer that can pull terabytes of data — the equivalent of multiple billions of rows of information — from servers and store it temporarily in random access memory, where it can be rendered useful to bank business analysts on the fly. The product picks up where SAS' JMP product leaves off.
It can also be extended, through a Web browser, to mobile devices including tablets.
By contrast, services such as Oracle's Exalytics are tied to servers, as well as Oracle's Exadata database boxes, and are meant for IT specialists. Such products don't yet have the client-side applications that SAS has developed, experts say. (Oracle was unable to make someone available to comment on this and other points.)
"The visualization piece, from a marketing perspective," makes the SAS product unique, says Michael Versace, a research director at IDC Financial Insights.
SAS, like its competitors, is tackling a fast-growing market. While the total business intelligence market has grown in the low double digits over the past few years and is currently about $12 billion, the data discovery subset, which includes such products as SAS' Visual Analytics tool, has grown by about 30%, according to Gartner. This market should approach $787 million by the end of this year.
"The time compression" from such products "is why there is such momentum around this," says Rita Sallam, a research vice president of business analytics at Gartner. "There is a great value proposition from allowing the business user to answer queries quickly and do analysis quickly, supported by in-memory."
Other vendors active with in-memory and visualization tools include International Business Machines, Microsoft, Oracle, Panopticon Software, SAP, QlickTech and Tibco Software. All of these offer big data analysis products that use in-memory capabilities, paired with some form of visualization tool.
And like many of the vendors producing in-memory products, SAS' product is integrated with the open source platform Hadoop MapReduce, which allows for distributed computing of large, unstructured data sets.
Google developers helped create Hadoop, and today it has become synonymous with big data analysis.
Hadoop MapReduce has "already gotten to the minds and hearts of data architects … and it's important for end users to see big vendors starting to incorporate this as a commercial offering," Versace says.
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