Data Mining or Data Extraction is the process of collecting, aggregating and sorting data. Its goal is to identify future correlations, patterns and trends.

This is a research field born around the 90s from the integration of some areas such as statistics, Artificial Intelligence and Machine Learning.

Data Mining applies to masses of data such that no human observer would be able to interpret them correctly and with criteria (Big Data). Thanks to the algorithms you get useful information from the data. In the case of companies, the use cases are numerous. You can identify buyer personas and links between products and services, anticipate the purchasing behavior of your customers and predict future trends.

We can distinguish two ways of extracting value from data, Descriptive and Predictive. The first notes similarities or shared groupings in historical data. The second method of Data Mining goes in depth and aims to classify events in the future or predict unknown results. Predictive modeling helps uncover information on how to avoid customer loss, and how to predict customer buying behavior.

Let’s look at some useful examples for companies:

Descriptive Mode:

  • clustering the types of customers
  • discover association rules between products and services
  • highlight sequential patterns of purchases over time.

Predictive Mode:

  • create future sales projections
  • identify deviations as in the case of credit card purchases. If there are deviations from the norm, the financial institution suspends the card.

Case History