Sifting a Riverbed of Data for InsightBy Kim S. Nash | Posted 2002-04-15 Email Print
Companies spent $4 billion last year on business intelligence software to synthesize and interpret a sea of data. Navigating among competing vendors who claim to do the job requires some intelligence as well.
Pizza-flavored cheddar cheesegood business opportunity? Yes, as Cabot Creamery determined. Does osteoporosis more often hit wine drinkers or teetotalers? Imbibers, as Kaiser Permanente can tell you. Will women who buy lace dresses by mail also buy lace bras that way? Not really, as Victoria's Secret knows.
Business intelligence software revealed the answers to these questions by synthesizing data that already existed at these companies, sometimes mixing it with outside demographic information, then analyzing it six ways to Sunday. The companies then made business decisions based on the results. Cabot started selling a new cheese, Kaiser looks for bone problems in heavy drinkers and Victoria's Secret knows not to push brassieres on certain customers.
Yet it isn't easy to sort through the hundreds of business intelligence products for sale. SAS Institute, the biggest vendor in this market and a specialist in statistical analysis tools, itself sells more than 50 products.
Some key categories include: tools to query back-end databases and build reports based on the results; data mining tools to pull specific variables from data sets; and online analytical processing (OLAP) tools, which are statistics tools that rely on multidimensional databases. Even everyday spreadsheets can do a lot of this work. Bankers, especially, love the spreadsheet method.
Product lines of the major vendors overlap in some areas and stand alone in others. Business Objects, for example, is known for easy-to-use query tools. Cognos has more complicated query tools, plus OLAP. Hyperio offers both an OLAP database and analysis applications designed specifically for finance tasks. Information Builders has a report writer and tools for gathering data from different sources.
Different tools are needed, depending on the kind of data available and what you want to find out.
For example, analysts would use OLAP to discover that there is a general tendency for two or more things to happen together. Beer, for instance, might sell better on hot summer days to men in their 20s. Identifying the population of those people in a geographic area to initiate a marketing campaign calls for mining of a demographics database.
Kaiser Permanente and other health care and pharmaceutical firms use statistics tools from SAS and various OLAP products. They study complex drug trials and patient medical information, involving dozens of variables that require traditional statistics techniques. As Sue Emmons, director of data intelligence projects at the Vancouver Coastal Health Authority, puts it, "We're not into widget management."
But other companies are, in essence. CVS Pharmacies, for example, tracks product sales at its 4,200 stores with an application built on Hyperion's OLAP database. Six hundred managers use it to find trends and streamline inventory.
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