Every day millions of data are being transmitted by the use of local area networks and the Internet. Aware of the voluminous demand for data storage, computer manufacturing firms regularly innovate file storage devices. They introduce new and more intelligent devices and gadgets to cope with this ever-escalating demand for storing and retrieving data.Despite their success in solving the data storage problem, companies are still hoping to use technologies that will provide them clear information on what really is going on in their businesses. Storing and retrieving myriad chunks of data are not enough to solve pressing business problems. Businessmen need useful information out of these.Owning data warehouses have partially solved this problem. A data warehouse is used to consolidate data found in different databases. This makes millions of data easily retrieved, interpreted, sorted and accessible by analysts. Though this device largely helps analysts, sorting and storing data are not enough to make most out of these data. They still cannot provide us with a clear picture of what is really going on in the firm and in the market (Alexander, n.d.).Turning numerous data into significant information is the aim of one of the latest technological breakthroughs in computers known as data fusion and data mining. These technologies enable firms to automatically search millions of data that they receive every day for patterns using tools such as classification, association rule mining, clustering, etc. (Data Mining, 2007). Data fusion is the method of integrating diverse data into a single, coherent representation of the tactical, operational or strategic situation (Cyr, 2006). We can say that data fusion is the first step in data mining. To find patterns, one should consolidate huge chunks of data to find out their similarities. This is exactly what data fusion is doing. Data mining divulges strategically hidden patterns found in huge amounts of data using high-end data analysis methods. It discovers new knowledge instead of testing assumptions that are suggested by users, which are being used by other business intelligence technologies (Sentient Information Systems, n.d.). It is an automated technology that allows exploration, analysis, and visualization of data of very large databases. Having the power to extract novel, implicit and actionable knowledge from large datasets, data mining is used for the discovery of non-obvious and finding out information and knowledge that can develop business processes. Having powerful capabilities makes data mining a very useful tool in business. It is used in sales/marketing, customer retention, buyer behavior, costing, quality control, inventory, and fraud (Williams, Hegland, and Roberts 1998).