Data mining
Data mining
Data mining, also known as Knowledge Discovery in Databases, is a set of techniques for analyzing large amounts of data, automatically or semi-automatically, creating an understandable structure and transforming this data into knowledge.
Data mining can be used to locate anomalies, patterns or correlations between the records of large amounts of data. With the information already analyzed, it is possible, for example, to predict results.
1. Advantages of data mining
Data mining offers many advantages Among the most significant advantages are:
- Obtaining very diverse information, allowing multiple combinations and offering results that would otherwise be difficult to access.
- Fast and reliable analysis of multiple databases with large amounts of data.
- The results obtained are easy to understand.
- Correctly processed data helps retain and attract new customers.
- It can be used to detect trends and patterns of behavior that help us improve various aspects of our business.
- The models obtained make it much easier to make reliable forecasts.
- This improves ROI and allows us to explore new business alternatives.
2. Uses of data mining in marketing
The marketing department is one of the main beneficiaries of proper data mining, as you can learn more about your target audience and customers, as well as create more effective digital marketing campaigns and send relevant newsletters.
Some examples of the uses of data mining, depending on the type of business, would be:
– Banks. Banks use data mining to analyze market risk by analyzing the data from each transaction, card movement or purchases.
– Medicine. By analyzing information from their patients’ records, they can offer more accurate diagnoses and speed up treatment/consultation procedures.
– Supermarkets. Supermarkets can analyze the purchases made by their customers, identify product associations or the best locations for certain products.