Big data refers to extremely large and varied datasets that grow rapidly and can include anything from text and images to numbers and sensor data. It is often described by the “3 Vs”:
- Volume: the sheer amount of data — think terabytes to petabytes, much more than standard databases can handle.
- Velocity: data flows in at high speeds from multiple sources, like social media updates, website clicks, or live sensors in real time.
- Variety: data comes in many types — structured (like spreadsheets), semi-structured (like emails), and unstructured (like videos or texts).
These characteristics make big data challenging to store, process, and analyse with traditional methods. Specialized tools and technologies, such as Hadoop, cloud computing and GPUs, are often used to process big data, making it possible to extract valuable insights that help improve products, understand customer behaviour, optimize operations, and even predict future trends.
Big Data is used to trained today’s most recent AI models, like Machine Learning and Generative AI models for tools such as ChatGPT.