Data mining, what is it?
Data mining is a concept that refers to the process of extracting useful and understandable knowledge from large amounts of data that are stored in different formats in order to find patterns of behavior. Data mining relies on mathematical models for the deduction of such patterns and trends, which are not detected through traditional data exploration because the relationships are too complex or the amount of data is too large.
Being surrounded by information does not mean that we are using the right information. Bill Gates
Stages of data mining
Data mining processes are carried out through four stages defined below:
- Know what the objective is and collect data. First, you must clearly define what type of information you want to obtain. Once defined, you must consider where you are going to collect the data you are going to work with.
- Data processing and management. To work, you need to have a representative sample of data to carry out the analysis and once selected, you must choose what type of variables or model to use on the sample.
- Choice of model. This stage is closely related to the previous phase. It tries to generate a algorithm with which, the best possible result can be obtained. An in-depth analysis of the variables to be used in the model must be carried out. Therefore, different tests of the algorithm such as time series or linear regression.
- Updating the model. It's the last phase. From time to time the model must be updated so that it does not become obsolete.
Advantages of data mining
Through the analysis of the data, patterns and trends can be applied in different areas such as the following:
- Product recommendations that can be sold together in addition to generating recommendations.
- Segmentation of customers or events into groups through affinities of the same.
- Selection of the best clients in order to offer them a more direct treatment either by email or telephone.
- Searching for sequences through products that customers have placed in the cart to predict future behavior.
Data mining and KDD
The acronym KDD (Knowledge Discovery in Databases) refers to the concept of Knowledge Discovery in databases which refers to the process of identifying patterns that are valid, useful, novel and understandable. Data mining is one of the steps that make up the KDD, where the steps must be consecutive as shown in the following image.
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