Metadata is essentially "data about data." It provides descriptive, structural, and contextual information, making other data easier to understand, locate, and use effectively. By capturing essential details—such as a dataset's origin, structure, purpose, relationships, and meaning—metadata enables data to be organised and contextualised.

Here is a key insight: Semantics gives data meaning. By adding semantics to the metadata, we make all metadata meaningful.

When discussing AI, we often focus on the algorithms—the visible 'tip of the iceberg.' But let's not forget what's submerged: a complex framework of data pipelines. The engineers who build and maintain these pipelines work tirelessly to clean and aggregate vast datasets. In fact, most of the grunt work often goes into this data preparation.