The emergence of the Internet allowed organisations to receive large quantities of data about their consumers, which can be used to enhance the efficiency of operations. However, in order to successfully interpret and use this information, it has to be collected and sorted correctly, which is the main task of data mining. Without an application of proper data mining techniques, one will be unable to use the information and make predictions regarding future trends and outcomes. The importance of data mining tools is connected to the meaning that data analysis has in terms of organisational value and improvement of processes.
The types of information they produce are – patterns and trends based on which one can make predictions about future demand or make recommendations regarding the company’s strategy. For instance, through association rule learning, one can gain insight into the relationships between different events. This can be used to gain insight into customer behaviour and improve the operations by targeting specific aspects that matter to the clients based on data.
Arguably, one should advise any company that collects large datasets regarding its customers to use data mining as part of their strategy. It is because this information can provide insight regarding the impact on the market and help the company understand its customers better. One example is an online shop with a large customer base, which can use data mining to determine purchasing patterns and preferences of their clients and tailor their offers, for example, advertisements or sales, based on this data. Therefore, in the contemporary world, merely collecting and storing data is not enough; organisations must use data mining to gain a more comprehensive understanding of their operations.