In times past, when thinking about digital data, it made sense to segregate data between transactional data, the data captured in business applications, stored in database tables and presented by BI tools, and all other data: emails, web pages, images, video and so on. Nowadays we tend to refer to such “other data” as unstructured data.

Nevertheless it was analyzable and software for deriving value from such data has crossed the chasm. It was that analytical imperative more than anything else which gave rise to the original concept of a data lake, a data store for both species of data and, additionally for data harvested from multiple sources external to the business, some of which was inevitably unstructured.