Metadata is defined as the information that describes and explains data. It provides context with details such as the source, type, owner, and relationships to other data sets. So, it can help you understand the relevance of a particular data set and guide you on how to use it.
I have clicked a snapshot in the evening time recently which I have used as an example to explain what is metadata. As you can see there is an image at first and the later part provides information about the picture like at what time it was taken, which device was used to click the picture, the focal length, size of the image, etc.
What are the types of metadata?
Metadata can be classified into the following types:
Technical: This includes technical metadata such as row or column count, data type, schema, etc.
Governance: This includes governance terms, data classification, ownership information, etc.
Operational: This includes information on the flow of data such as dependencies, code, and runtime
Collaboration: This includes data-related comments, discussions, and issues
Quality: This includes quality metrics and measures, such as dataset status, freshness, tests run, and their statuses
Usage: This includes information on how much a dataset is used, such as view count, popularity, top users, and more