Big data refers to datasets so large, fast-moving, or structurally complex that conventional databases and data-processing tools can't handle them efficiently. It's often described through the "three Vs": volume (the sheer amount of data), velocity (how quickly it's generated and needs to be processed), and variety (how many different formats and sources it comes from, structured, unstructured, text, images, sensor readings).
Big data and modern AI are closely linked, since large machine learning models, especially large language models, depend on massive training datasets to learn effectively, and the specialized infrastructure originally built to store and process big data, distributed computing, cloud storage, and parallel processing, is largely what makes training today's largest AI models computationally feasible at all.
