One of the most recurrent and abused phrases of recent years is that data is the new oil . However, there is some truth in this, as long as you know how to select and take advantage of this enormous information potential . In this, data mining is the most important activity.
What is Data Mining?
Data mining crosses statistics, artificial intelligence, database management : it is a part of the Knowledge Discovery in Database process , which includes data selection, preprocessing and transformation, then data mining, finally pattern recognition, interpretation and knowledge acquisition.
Data mining, in particular, is literally ' data extraction ' , i.e. the process of selecting, exploring and analysing data to obtain useful information from large amounts of data. This activity finds correlations and recurring patterns between data coming from often heterogeneous sources, through the use of machine learning algorithms. Aspects of preprocessing and data management, in addition to the analysis itself, are therefore included in data mining.
Advantages of data mining
The main advantage of data mining is its power to identify patterns and relationships in large volumes of data from multiple sources . With an ever-increasing amount of data available from diverse sources such romania whatsapp data as social media, remote sensing, and increasingly detailed reports on product movement and market activities, data mining offers the tools to make the most of Big Data and transform it into usable intelligence.
The process of data mining allows us to detect surprising relationships and patterns in seemingly unrelated pieces of information. Because information tends to be compartmentalized, it has historically been difficult or impossible to analyze it as a whole. However, there may be a relationship between external factors (demographic or economic) and the performance of a company's products. Cross-referencing all this information allows us to think outside the box and gain competitive advantages through innovation.
In fact, while managers regularly examine sales numbers by area, product line, distribution channel, and region, they often fail to consider the external context for this information. Their analysis highlights “what happened” but does little to uncover “why it happened this way .” Data mining can fill this gap and help guide product, channel, and production decisions. The same analysis benefits other parts of the company, from product design to operational efficiency to service delivery.
Data mining
Differences between Big Data and data mining
Although they are strongly interrelated, Big Data is distinguished from data mining, which indicates the computational process of discovering patterns in large data sets using machine learning, artificial intelligence, statistics and database methods.