Case Study 1: Data Mining

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Data mining can provide companies with priceless information. It can predict trends of how sales will go or even what purchase someone will be making in the future. If you look hard enough, you can glean even more information about the personal lives of the individuals. Data mining can truly drive businesses into the future in all areas. Predictive analysis is a process that makes decisions more of a science than a guessing game. In fact, it is a multi-step process that is designed to spot the problem, explore data sources, find patterns, use the information to build a model, extract the valuable information to generate useful algorithms in order to construct a predictive model, and deploy it. This process allows companies to streamline the ability to access and process mass amounts of data. This helps prevent fraud by consumers, identify risks and even look where to market to consumers in the future. Being able to predict risks that could negatively impact a company ahead of time could save money in the future. This type of algorithm allows businesses to beta test many scenarios, cutting years off of normal testing time. Being able to predict consumer behavior gives a competitive advantage that helps the company stay ahead of the competition. Association analysis is helpful in discovering useful relationships concealed within metadata. It is important to remember that discovering patterns from a large data set can be time consuming and expensive to compute. Also, sometimes there is actually no pattern, only coincidence. On a smaller scale, association discovery takes a closer look at the relationship between items in a single transaction. A good example is market-based research, which is used to drive search engine ads and recommendations. This type of research is used to make suggestions based on things already searched for or purchased. This type of

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