You may think you are using your data warehouse to its fullest extent. You have amassed a great deal of information about customers or inventory, and you are able to look up information at will.
However, without the use of the proper business intelligence tools, your data warehouse is nothing better than a hunk of coal. By using business intelligence tools such as data mining, you can turn that coal into the diamond that can propel your business to the top.
There is no question that data mining can help a company do more than it ever realized with its data warehouse. Some call it data mining, while others call it data discovery or data knowledge. No matter what you call it, the concept is the same: It allows you to take your data warehouse, dissect it piece by piece and summarize it into useful information.
Keep in mind that data mining is not just a fancy term for online analytical processing. While OLAP tells you what happened in the past, data mining helps users predict the future through the discovery of trends and patterns in the data. This insight can help a business repeat good trends and avoid bad trends. Most business users will use a combination of data mining and OLAP. It’s important to keep in mind the difference so that the proper tool is used to answer the question at hand.
Data-mining tools are especially important for marketing departments, because marketing efforts succeed when they single out customer segments with high profit potential. Previously, it was difficult to identify these groups, because it required sifting through large amounts of data manually. With data mining, it is easy to sort through the data and discover customer behavior and patterns quickly.
For example, if a company is examining the effectiveness of its advertising campaign and wants to find out why people are coming to its Web site – and who is buying products – data-mining tools can help. Data mining lets that company sort through its data warehouse to profile its customers in such a way that it can find out which referring Web sites generate sales and which ones do not. This helps the company better target its future marketing efforts.
Data mining also can directly affect a business’s bottom line by improving quality. The analytical features of data mining allow business leaders to identify best practices that are hidden in their data, institute fraud control and support initiatives that center on operation improvement. Data-mining tools are new weapons that weed out inefficiencies and help a company outpace the competition.
There are several data-mining tools out there. Some of the more popular tools are Cognos Scenario, Angoss Knowledge Suite, Business Objects Business Miner, SAS Enterprise Miner and SPSS Clementine. In addition, Microsoft SQL Server 2000 will have data-mining features. There also are related tools that do predictive modeling or present the results of the data mining graphically, and even Microsoft SQL Server, when used with Excel 2000, presents data-mining possibilities.
But which program is best?
There really is no answer to that.
The best program for you may not be the best program for another company. It depends on the level of management and sophistication you need. If you are a visual person who needs to see it in a graph, you want something like Cognos Visualizer. If you are a person with many thoughts, but are not sure where they lead, you may want to use Cognos Forethought.
To use data-mining tools, you need to clean up your data warehouse and then integrate it into one database. Then figure out which type of data you will use. Once you have your core listing of data cleaned and ready, you need to transform it into the appropriate form for use by the mining tool.
When you start mining, you use a pattern finder to figure out what types of patterns exist in your data. Once you find some patterns, your last step is to figure out which are useful and interesting and which are not. This process may take some time.
The use of data mining is still up and coming, but it is becoming clear that without data-mining tools, businesses are not getting all they can out of their data. The growth of e-commerce has increased the need for data mining because Web-based companies are amassing huge amounts of data on their customers that would be impossible to analyze with traditional tools.
You must remember to keep the key decision-makers involved during the entire data collection and mining process. This is because they will be the ones using the data and they need to know how to use it. Think of decision-makers as the miners with the helmets and lights. You can send them into a cave, but if you don’t tell them what to dig for and how to do it, they won’t find anything.
Michael C. Pelletier is a consultant at Pinnacle Decision Systems, Middletown, CT, a privately held professional services and software development company.
