Data mining is a systematic approach to collecting, organizing, and analyzing data sets to find patterns and relationships. It helps organizations predict future trends and improve processes. A properly designed data mining system applies user-defined goals or business models to the data and provides analysis of the most relevant information. Companies use data mining to increase profits by targeting specific customers and refining their data collection methods.
A data mining system is a systematic approach to collecting, organizing, and analyzing data sets. Finding patterns and relationships in collected data is the object of data mining. The patterns and relationships discovered help organizations predict future trends based on past patterns. While these models can be useful for forecasting purposes, inaccurate models occur when the raw data used for analysis is corrupted, misclassified, or does not contain the samples needed to produce accurate results.
Applying a data mining system to previously collected data requires the creation of a structural design. The data is then filtered through the architecture. If a robust architecture is in place, the filtered data will reveal patterns and meaningful relationships among the data. Before the advancement of data mining systems, data was collected and delivered to the user as-is; however, a properly designed data mining system applies user-defined goals or business models to the data and provides analysis of the most relevant information. After further distillation by the system, this information can be used to plan future activities and to evaluate the potential success or failure of those activities.
By focusing on data mining, consumer-oriented companies operate with greater efficiency. For example, because a data mining system allows analysis of data trends, in the food industry this could be an analysis across product types in relation to a specific type of shopper. Noticing these trends allows the company to predict buying cycles based on the relationships in that group. For example, if a local grocery store discovered through its data mining system that working mothers often come on Tuesdays to buy frozen pizza, then they could target that group by moving the frozen pizzas to the front of the food display frozen on Tuesdays. This small action has the potential to boost the grocery store’s profits.
The uses of data mining systems are varied. From the surveillance of terrorists to the improvement of the game with video games, data mining enables improvements in processes and strategies that directly influence the user experience with the product or service. A large number of companies use data mining to increase profits by targeting specific customers who are more likely to purchase specific items, so these companies focus on getting those customers into the store to make purchases. Obviously this allows the company to collect even more data from these customers and they can further refine their data collection methods.
Protect your devices with Threat Protection by NordVPN
