Big Data is already one of the biggest trends for banks and financial institutions, with several benefits for business. Data Mining is one way to extract information that can be used to treat Big Data.
Data Mining (or data mining) is one of the ways that computing has found to deal with the growing volume of data that users have generated. It is a process that seeks to organize data, find the most important ones, and, based on that, trace relevant relationships between them and recognize behavior patterns.
For this, the software works together with information scientists and management professionals. These programs use some gimmicks, such as artificial intelligence, statistics, and machine learning, to analyze raw data and produce information that can be used to understand customers better and generate new indicators for the company.
How Does It Work?
In practice, we can use the following situation to exemplify Data Mining: a company in the financial area that aims to create a classification model that lists customers who make payments on time, those who pay late, and those who do not. Pay.
The project model is based on the history of these consumers and a predetermined period for analysis. So, here we have patterns of behavior repeated among several customers — each one falling into one of the 3 groups mentioned.
Using Data Mining in this project is essential to create an efficient model capable of presenting data more clearly, thus facilitating decision-making and the creation of new strategies based on the notes made.
Prediction capability is another benefit of Data Mining that can be seen in practice, especially in companies that must deal with prediction models, such as stocks, quotes, sales, and other products with variable indices.
Regarding security, another very important Data Mining mechanism nowadays, especially with many online transactions, is its use to help detect credit card fraud. However, how can he do this? Based on the customer’s previous behavior, since his purchase profile is reflected in the card’s history, showing a certain regularity.
For this reason, any sudden change in this curve already draws attention. This greatly enhances fraud detection, thus bringing more security to all parties involved.
What Is The Relationship With Big Data?
Generally, data mining is done with smaller samples, which limits the number of results it can offer. Big Data analysis is a process similar to what is done in Data Mining but on a larger scale concerning the amount and type of data.
Mining is best used with more structured data, such as spreadsheets and relational and dimensional databases. Conversely, big data work with more complex and unstructured data, which must also be registered in a database.
As the scales and data types differ, the analysis periods and results also differ. While Data Mining refers to a more punctual process, which generates reports, pointing to specific issues, Big Data is an analysis carried out continuously for longer periods. For this reason, Big Data can be used to make predictions and indicate paths for strategic changes in management.
Data Mining In Companies
It is currently seen as a major competitive differentiator by many companies. That’s because, according to a study by Gartner, the volume of data and information has been growing exponentially over the years, as well as its importance for business.
So much so that the data will be considered part of the corporate assets in up to 5 years, thus, it is unsurprising that investments in this technology have gradually increased in recent years.
For example, companies like Google and Netflix have strategically used this to conquer their space in the market. Furthermore, according to a survey carried out by the consultancy IDG, 92% of managers and executives plan to expand their investments in data mining.
