If you think about the word ‘data’, you immediately associate it with information. Of course, the two terms are synonyms, but only partially. Actually, data is anything that can be related to facts, number or text, which can be further processed by a computerised machine. This type of information is extremely important, especially for those who work in big companies and need to use that data to certain purposes. For this reason, organisations nowadays are gathering vast amounts of data, in several formats and types of databases. Processing these pieces of information is very important, which is why there are many tools and pieces of software used to data. Among these, one of the most popular is data mining.
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What is data mining?
Data mining is the operation companies perform, in order to transform raw data into useful pieces of information. Sometimes, this specialised process is also defined by the term ‘data / knowledge discovery’, since it analyses certain variables from different perspectives and then summarises them to provide the results demanded by the user. The evolution of technology has facilitated the emergence of dedicated data mining software
, a tool used by experts to search patterns in huge batches of material. This program is formed of a series of analytical tools that can assess the information from many different angles and dimensions, classify it and offer niched results. This is way businesses can get particular details about their clients, stakeholders or about the market in general, so that they can develop more efficient marketing strategies. As a matter of fact, data mining means not only summarising information, but also creating interconnections and establishing patterns in a large storage structure.
Why do companies need data mining?
Taking into consideration the huge amount of information that a company can gather in their databases during many years of existence, data mining and extraction play a crucial role for its evolution. It helps them dig, extract relevant pieces of information and classify them, not to mention that it can spare a lot of time and efforts, due to the automated software that can perform the operations. It can analyse multiple types of data, both transactional and operational. Here are some examples: sales, costs, payroll, accounting results (industry sales, forecast data), inventory, meta data and so on. To sum up, data mining can be compared to a market analysis, except the fact that the information is extracted from the internal, not the external environment. That is why a professional data mining process can help a company increase customer service and clients’ loyalty and unlock hidden profitability resources. In addition to this, it can also help organisations reduce client dynamic. All these relevant results are further used to understand customers’ needs, develop marketing campaigns, increase sales and thus reduce costs. All in all, it is a simple, time and cost efficient method of getting information about the external environment, by using internal resources.