Data Mining and Its Value Process for Business Management

In the midst of a digital transformation that leaves traces in its wake, data management could not be left behind, it can be daring to affirm it, but information is the cornerstone that defines not only new strategies, but also promotes the development of innovations in technology that marks a growing trend in categorizing, debugging, transferring and storing processed information with the aim of guiding decision-making aimed at business growth, knowing more about the end customer and even doing the unthinkable until a few years ago … predicting what will happen to our consumer trends, foundations of business productivity.

The panorama is broad so that we will limit the management of the information from its mining, that is from its extraction process known as Data Mining or data mining.
What is Data Mining?

It is a process framed by the Fourth Industrial Revolution, in which technology and applied techniques are used to efficiently explore a large volume of data.

Artificial Intelligence has been applied in its exploration because based on it, it seeks to predict the behavior of the market through the results thrown by the data that comes from customers or consumers.

The mission of Data Mining is to structure information, under a previous extraction of raw data that is transformed into a qualified data, based on statistical processes and AI that yield interesting metrics for the prediction of market models and taking business decisions.

Let’s see 4 the processes that involve the operation of Data Mining, which allow to consolidate decision making.

  • Determination of Objectives: Focuses on the main objectives by which data extraction focuses on specific areas: Marketing, Research and Development, Financial and Production.
  • Data Processing: Application of technologies and mathematical tools such as, Artificial Intelligence and statistics.
  • Establishment of Model: Are the behavior patterns that manage to model or predict the behavior of the data.
  • Analysis of Results: Through the process of data and information purification, detail the possible strategies and actions to be taken based on the results obtained.

What is the value management that adds to the organizations the application of Data Mining?

The irruption of the large volumes of information coming from the growing management in the Cloud and its derived interactions with the corporate environment, have led organizations of all sizes to seek to overcome the barriers of data management, so that channel the opportunities to open digital scenarios where information is of quality, reliable and easily accessible.

At this point we stop to estimate the management values ​​that Data Mining brings to corporate management.

Support for the definition of corporate objectives, which will seek to be achieved with the support of the efficient management of business data.
KDD (Knowledge Discovery in Database), this process allows the identification of useful patterns in the data that after becoming information, promotes knowledge and allows to plant the bases of the forecast in the behavior of the data and typing in the behavior of the market.
Increase knowledge and understanding of information, facilitating access and reading for each of the users
It makes it possible to share information in systems such as ERPs and CRM across the entire organization.
It stipulates security protocols for the storage of information, as well as its access in a secure manner as well as the modifications to the data that are required.
Reduces redundancy of data and information by more than 90%, developing the concept of the Unique Data.

The value management that integrates Data Mining supposes a management protocol for its guarantee of success in the extraction of data and its conversion into information.

A standard protocol assumes:

  • Understanding of the business core of the organizations that apply this technical process.
  • Determination of the way of obtaining and filtering the data.
  • Establishment of the mathematical models (algorithms that will typify the information besides the model) and statistics like correlation of variables, Chi square and linear regression.
  • Validation of the models obtained based on verification of compliance with the proposed objectives on forecasting and market behavior.
  • Integration of the data, this by the results of validation favorable to the projects and corporate objectives.

The innovation of technology that is aligned to the corporate development in areas such as Artificial Intelligence, Big Data and storage solutions such as Cloud, Fog and Blockchain are allied so that the extraction of raw data provides companies with total forcefulness of truthful information and capable of creating new business environments such as those observed in the B2C environment; whose electronic commerce platform is more fluid and allows predicting buying behavior in the market for mass market organizations, not so much as in B2B, but it makes possible a typification of transactions focused on strengthening commercial relationships between partners and business partners.

We leave you with a phrase that frames data mining and tells us about the strength of information in the era of Digital Transformation and the Fourth Industrial Revolution

“Authentic genius is the ability to evaluate uncertain, random and contradictory information.”

Winston Churchill