Big data refers to data that would typically be too expensive to store, manage, and analyze using traditional (relational and/or monolithic) database systems. Usually, such systems are cost-inefficient because of their inflexibility for storing unstructured data (such as images, text, and video), accommodating “high-velocity” (real-time) data, or scaling to support very large (petabyte-scale) data volumes.

The ability to consistently get business value from data is now a trait of successful organizations across every industry, and of every size. In some industries (such as Retail, Advertising, and Financial Services, with more constantly joining the list), it’s even a matter of survival.

Data analytics only returns more value when you have access to more data, so organizations across multiple industries have found big data to be a rich resource for uncovering profound business insights. And, because machine-learning models get more efficient as they are “trained” with more data, machine learning and big data are highly complementary.