With commercial database growing at unprecedented rates, data mining is the new buzzword in the business world. It is a powerful mechanism that helps to automatically evaluate huge data to discover patterns and trends that helps the companies to focus on the most important information in their database and make proactive informed decisions. It saves time and also predicts unexpected facts that help the businesses to explore newer ways to generate more revenue.
The key properties of this technology include automatic discovery of patterns, prediction of likely outcomes, creation of useful information and focus on large data sets and databases. This easy to implement solution is instrumental in predicting trends and behaviors that helps in target marketing to identify the most potential promotional strategies and even forecast future predicaments like bankruptcy. It also helps to trace unnoticed patterns for example evaluating retail sales to find out products that are purchased together.
Data mining uses a technique called modeling to predict these trends wherein a model is developed in one situation where the outcome is known and then putting the same model into another situation to predict the outcome of that situation. The software scans all the data in the computers and extracts characteristics of the data that should go into the model.
Once the model is built, it can be applied to similar situations to predict the outcome. Data mining also identifies natural grouping within the data. The companies require fully integrated data warehouse as well as flexible interactive business analysis tools.
The process starts with data warehouse that contains information about the entire customer base as well as market updates about the competitors. On-Line Analytical Processing (OLAP) is a tool that used for analyzing shared multidimensional data such as cost allocation, data summarization, time series analysis, what-if analysis and full support for hierarchies. The difference with data mining lies in the fact that data mining does not have the concept of dimensions and hierarchies. Data mining software should be integrated with data warehouse and OLAP to bring out ROI-focused business analysis.
Through the process of integration with the data warehouse, operational decisions can be directly implemented and tracked. As the warehouse grows with new decisions and results, the organization can continually mine the best practices and apply them to future decisions.
There is an explosion of information pertaining to customer, supplier and market information. The need of the hour is timely and sophisticated analysis of this unfathomable bulk of information. There is a gap between the data storage, retrieval systems and the users’ ability to analyze and act on the information. Data mining tools have proven to be useful to businesses by bridging this gap and opening up new ways to get the sales figure shoot higher.
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