One of the problems that many companies face today is the difficulty of efficiently organizing their data repositories and, therefore, taking advantage of them to create the most appropriate business strategies to attract new customers or retain loyal customers. that they already are.
These data repositories sometimes become difficult to manage or process due to the massive collection and accumulation of information that companies make from their users. And it is, in circumstances like this, when Data Mining (or Data Mining) can be especially useful.
If you want to know what Data Mining is and what it is for, how to implement Data Mining in your business and what are its advantages, keep reading this article that we have prepared.
WHAT IS DATA MINING AND WHAT IS IT FOR?
Data Mining is a set of techniques and technologies that are used to explore within a data repository, in order to find patterns of behavior, trends or rules, understand them and transform them into relevant information that companies and institutions can use to implement improvements or seek solutions and, in this way, achieve your business goals.
It is an automatic (or semi-automatic) process that combines, mainly, computational analytics and statistics, Artificial Intelligence and Machine Learning.
Some of the main applications of data mining are found in the retail trade, the banking sector and financial services, as well as in health management or Marketing strategies, among others.
DATA MINING PROCESS: 4 STAGES
1. SETTING THE OBJECTIVES AND / OR PROBLEMS
This phase consists of determining the problems or the possibilities of improvement of an organization and thus establishing a plan to carry out the Data Mining.
2. COLLECTION AND PREPARATION OF DATA
Once you have decided what data you want to collect, it is time to collect it and, with this, know the current situation of the problem, the objective you want to achieve and what is needed for it.
Next, it is identified if there are quality problems in the data (duplication or lack of information, inconsistencies, etc.) to clean up or add some more, look for patterns and give them the appropriate format for the modeling phase.
3. DATA MODELING
At this stage of the Data Mining process, these are processed through the implementation of mathematical algorithms, statistics, Artificial Intelligence, etc., in order to establish analogies.
If for any of those the system detects a problem with the data, it would be necessary to go back and perform the previous step again.
It is time to check if the results of the analysis are coherent and help to achieve the previously established goal, or if they provide new and relevant information for decision-making.
WHAT ARE THE BENEFITS OF DATA MINING?
- Automatically or semi-automatically analyze very large data repositories.
- Discover relevant information for business strategy.
- Find and attract new users.
- Build loyalty / retain old customers.
- Improve customer service based on the information obtained
- Optimize the offer of products and / or services to the needs of users.
- Save costs and time for the company
- Open new business opportunities.
BIG DATA VS DATA MINING: HOW ARE THEY DIFFERENT?
Although both concepts have a lot to do with managing large volumes of data, the truth is that they are used for different purposes.
|Big data||Data Mining|
|Collection and storage of large amounts of data so that it is available to the company or organization.||Data analysis. Identification and extraction of relevant information from Big Data.|
If you want to learn more about Data Mining or Data Mining, do not hesitate to download our e-book Expert Course in Web Analytics for free . It is completely free and has been written by Alejandro Magdalena, director of the Master in Web Analytics at the European University (in Bootcamp format).
And if you want to go further, our academic offer also includes other specialized degrees in this sector, for example:
- MASTER IN BUSINESS ANALYTICS
- MASTER IN BUSINESS ANALYTICS ONLINE
Do not miss the opportunity to train in a profession for the future!