Big Data

Big Data (or large-scale data) are data sets with such high and complex volume, velocity, and variety that they cannot be managed, processed, and analysed using traditional data processing methods and tools. They are typically characterised by the "3 Vs" – Volume, which indicates the massive quantity of data; Velocity, which relates to the speed at which they are generated and transmitted, often in real-time; and Variety, which refers to the diverse sources and formats (structured, unstructured, semi-structured).

What is it for / Why it is Important

Analysing Big Data, often performed with the aid of advanced technologies like Artificial Intelligence and Machine Learning, is fundamental for extracting significant information and insights. It allows companies to make more informed, data-driven decisions, identify patterns and trends, and gain a deeper understanding of customer behaviour and preferences.

When it is used / In what context it is useful

It is used in all sectors where the quantity of data generated is massive and the goal is to derive strategic value from it. In marketing, it is crucial for customer profiling, personalising campaigns, retargeting, and optimising marketing automation strategies. It is also essential in the financial sector for fraud detection, in logistics, in manufacturing (predictive maintenance), and in scientific research.

Practical Example

An e-commerce company analyses a massive volume of data generated by purchase transactions, website browsing behaviour, social media interactions, and online reviews in real-time. Processing this Big Data allows it to predict which products a specific customer is most likely to buy and, consequently, to send them personalised offers or display targeted advertisements (retargeting) in a matter of seconds.