What is the importance of "Data Mining" and why does correct information generates value?

Luis B.

Published Apr 4, 2023

The data mining process consists of discovering patterns, trends, and useful information in a large dataset. The process of generating such value consists of several steps and compared to the foundation of a construction, it is based, by definition, of what is necessary in terms of volume, speed, variety and veracity of the data (efficiency and effectiveness).

The purpose of grouping and analyzing a large amount of data goes far beyond reading metrics and status. Its importance expands to the objective:

1- Identification of new patterns and trends hidden in the data.

2- New 'insights' and new opportunity scenarios that become knowledge.

3-Identify bottlenecks in processes, transactions, production, and services.

4-Create forecasts to support early actions to the new trends identified (or or predicted).

The management of data quality is the key to data mining process with the purpose to keep high quality, accuracy, absence of 'bias' in the data and support the decision making. Know your customer´s objectives and intentions, converges to the creation of a database that will support and validate the key actions to maximize all efforts for a good model, to provide valuable information for the business. Therefore, building a solid base of relevant and reliable data is fundamental to the success of a data mining process.

Starting with the basics is essential. In many cases, sophistication, and complexity in data modelling, at least at the beginning of the project, is not the key factor. It's about much more creating a better experience for your customers.

The experience of build value using data mining is enhanced when we begin to understand the reason we are doing something, in this case nothing better starting with "Why". Understand the reasons and ambitions of a project is the success key factor for a good project of data mining implementation. Incorporating continuous intelligence into the process of improving decision-making is the differential in any sector. Data becomes information, which in turn becomes knowledge and finally becomes better strategies.