Big data refers to datasets whose volume, velocity, variety, or complexity exceed the capacity of traditional data-processing tools. It often requires specialized infrastructure, analytics techniques, and governance controls for storage, processing, quality management, and interpretation. In AI, big data can improve statistical power but can also increase risks such as false discovery, privacy exposure, and hidden bias.
A term used to refer to data sets that are too large or complex for traditional data-processing application software to adequately deal with. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data is often characterised by the volume, velocity, and variety of data, requiring specialised tools and technologies for effective storage, processing, and analysis.