Data mining – is it new business? The answer is ‘far from it’. Actually, data mining is no business at all – it is just a business process that helps businesses enhance their performance.

But you can initiate a new business if you can successfully mine the right kind of data from your well organized data warehouse; though the job resembles searching for the needle from the backyard haystack. However, it is the latest business buzzword that is drawing business persons ranging from greenhorns to great gamblers like never before. However, the needle at this instance is that small but essential intelligence or aptitude, whatever you may call, that is necessary to develop your business while the haystack represents your database or data warehouse that you have created over much time.

Using automated methods of statistical analysis which may be termed as a form of data mining, business people are now in the process of finding out new trends or drifts in business related behaviors that was earlier ignored. As soon as this is achieved, it can be utilized in a prognostic manner to newer business ventures and also sometimes for the present business itself to find tune it and enhance its productivity.

But the first step towards reaching the goal, as you may appreciate, requires the right kind of data or information that is relevant to the business to be gathered. Although it may sound difficult at first, it is not that hard to get into it. After all, it is your business and you’re the best judge to see what data is pertinent to your business. If you are selling shoes, for instance, you would know who makes them best, which community prefers them more or which is the best selling season. And once these information or data is gathered, use your spare time to hone them or edit them till you reach the gist. If you are presently tracking the date of the customer in a contemporary DBMS, you have probably finished with it. That means you have already created your own data warehouse.

Now is the time for experimentation. Select one or many algorithms to match your problem with the data in hand. Algorithm, as you may understand, involves repeated step-by-step application of a process till one reaches the solution. Since you are experimenting with several methods, chances are, one of them will click. Or you may go for two of the most common forms of algorithms, namely, Regression and Classification. The first one is the commonest statistical technique adopted by those into data mining the world over. It involves selecting a numerical dataset & developing it into a mathematics formula that agrees with the data. As you feel the results are ready to be used for forecasting the behavior, take your current data, plug this to a developed formula & you have reached your goal! However, one of the major drawbacks related to this method is that the system works great with continuous data in quantities only. When you are working data that is categorical and the order is not crucial, you would do well with other techniques.

When you are using categorical data or may be a combination of continuous categorical and numeric data, Classification will suit you fine. It is quite competent in processing a much wide kind of data as compared to Regression and so is becoming more popular with the new breed of business community. Instead of pursuing a complex mathematical formula to reach a decision, it provides you with decision tree, requiring many binary decisions.

Data mining, as said earlier, is an oven fresh topic now. Apart from Classification and Regression, many other algorithms for data mining have hit the market like bomb shells now.

Products of data mining products are the big thing today. Most database distributors have taken adequate steps to see to it the platforms can use the techniques for data mining.

Oracle’s Data Mining Suite (Darwin) already includes Neural Networks, Classification and Regression trees, Regression Analysis, k-nearest neighbors and detailed Clustering Algorithms. The SQL Server of Microsoft allows data mining by using clustering algorithms and classification trees. Data mining algorithms are on offer by many statistical packages such as S-Plus, SAS and SPSS.

So, you can see that data mining is no business but much more than that. In today’s competitive world, data mining has become something very important as it enables a business to perform better and give it an edge over competition.