Today, we often hear the term “Big Data,” and alongside it, the phrase “Machine Learning” is frequently mentioned. What exactly do these terms mean, and how are they related? Let’s clarify!If we translate it literally, “Machine Learning” means “automatic learning.”
Machine learning is based on the idea that machines, meaning computers, are capable of learning and providing results based on mathematical algorithms that are given to them, almost like specific instructions to follow in order to generate an outcome. Over time, the evolution of Machine Learning has led to its application in the field of Big Data, which refers to sectors dealing with large volumes of data, as well as in data mining and predictive analytics.
An example? Let’s take a company involved in marketing and sales. Through its website, it can gather information about customer purchases and searches. At the same time, using algorithms, this data can be extracted and used to personalize marketing campaigns or customize the customer’s shopping experience.
Another case where Machine Learning and Big Data are used is in financial companies. In addition to gathering information about customers, these companies can leverage these techniques to predict future sales trends.
According to experts*, adopting Machine Learning algorithms within a company can increase revenue by 3% annually. This would lead to a 23% growth in Italy’s GDP by 2030, compared to the baseline of 2017, creating a national economic advantage. For companies that individually adopt these new technologies, their profitability will improve relative to competitors who fail to keep up with the times. This growth is expected to be seen across all sectors.
