Data mining: understand what it is and how it is essential for Data Marketing
Posted: Tue Apr 22, 2025 4:28 am
There are a variety of data sources inside and outside organizations. But addressing a more specific universe, within a company there is countless data. Just imagine: a sales department spreadsheet is data, media reports are data, CRM information is data. However, it is undeniable that direct access to this information allows us to have raw data, often full of noise and without a defined format, making it difficult to understand.
This is where data mining comes in. For those unfamiliar with the subject, data mining is a set of computationally applied techniques that search for data and model it into a readable form. Data mining techniques aim to discover new patterns and perceive patterns that have already been defined.
In other words, through statistical el salvador mobile database methods and with the help of artificial intelligence, machine learning and database queries, mining becomes possible efficiently according to a specific objective.
Before we delve into data mining itself, it is important to go back to the concept of what data is. Let's go:
What is Data
Data is any type of fact, number or text that can be processed by a computer. Today, organizations produce exorbitant amounts of data every second in a variety of formats. Furthermore, as we have already mentioned, data can be found in a variety of sources, including:
Operational and transactional data such as sales, costs, inventories, payments and accounting;
Non-operational data, such as forecast data and macroeconomic data;
Metadata is data that talks about the data itself. A good example of metadata is how it should be considered in relation to its format (01/02/2016 day/month/year).
The information blocks
Operational data associated with non-operational data and metadata allow the definition of patterns capable of constructing blocks of information.
Sales information for a given period can, for example, be associated with forecast data to define action strategies. In addition, through the specification or use of existing metadata, it becomes possible to format the information.
As in the previously mentioned example of metadata, we have the specification of how a date should be considered, dd/mm/yyyy. In other words, through that pre-established format, we know that the date information must follow the day/month/year pattern and that the day must have 2 digits, the month 2 digits and the year 4 digits.
Metadata functions as a descriptor that contains the form that data must contain in order to be understandable. It is like an instruction manual for a specific piece of data where we know what it means and how it should be stored. To effectively read a piece of data, we need to know how it should be read and evaluated, and this is also essential for its storage.
This is where data mining comes in. For those unfamiliar with the subject, data mining is a set of computationally applied techniques that search for data and model it into a readable form. Data mining techniques aim to discover new patterns and perceive patterns that have already been defined.
In other words, through statistical el salvador mobile database methods and with the help of artificial intelligence, machine learning and database queries, mining becomes possible efficiently according to a specific objective.
Before we delve into data mining itself, it is important to go back to the concept of what data is. Let's go:
What is Data
Data is any type of fact, number or text that can be processed by a computer. Today, organizations produce exorbitant amounts of data every second in a variety of formats. Furthermore, as we have already mentioned, data can be found in a variety of sources, including:
Operational and transactional data such as sales, costs, inventories, payments and accounting;
Non-operational data, such as forecast data and macroeconomic data;
Metadata is data that talks about the data itself. A good example of metadata is how it should be considered in relation to its format (01/02/2016 day/month/year).
The information blocks
Operational data associated with non-operational data and metadata allow the definition of patterns capable of constructing blocks of information.
Sales information for a given period can, for example, be associated with forecast data to define action strategies. In addition, through the specification or use of existing metadata, it becomes possible to format the information.
As in the previously mentioned example of metadata, we have the specification of how a date should be considered, dd/mm/yyyy. In other words, through that pre-established format, we know that the date information must follow the day/month/year pattern and that the day must have 2 digits, the month 2 digits and the year 4 digits.
Metadata functions as a descriptor that contains the form that data must contain in order to be understandable. It is like an instruction manual for a specific piece of data where we know what it means and how it should be stored. To effectively read a piece of data, we need to know how it should be read and evaluated, and this is also essential for its storage.