The 3 types of metadata to master to be a data-centric enterprise!

Metadata is structured information that describes, explains, tracks, and facilitates the access, use, and management of an information resource. The most frequently cited definition is, “data on the data.” In a data-centric approach, what types of metadata does an enterprise have to make available to render data consumers more autonomous and productive?

Our definition of metadata

Metadata is contextualized data. In other words, they answer the questions of “who, what, where, when, why, and how,” of a data set. They must enable both IT and business teams to understand and work on relevant and quality data.

What are the three types of metadata?

At Zeenea, we speak of three types of metadata within our data catalog. Here are, among others, some examples:

  • Technical metadata They describe the structure of a data set and storage information.
  • Business metadata They apply a business context to data sets: Descriptions (context and use), the owners and referents, tags and properties with the goal of creating a taxonomy above the data sets that will be indexed by our search engine. Business metadata are also present at the schema level of a data set: descriptions, tags, and even the level of confidentiality of the data by column.

  • Operational metadata They make it possible to understand when and how the data was created or transformed: Statistical analysis of data, date of update, provenance (lineage), volume, cardinality, identifying the processing operations that created or transformed the data, the status of the processing operations on the data, etc.


Metadata management is an integral part of an enterprise’s agile data governance strategy. Maintaining an up-to-date metadata directory ensures that data consumers can use reliable and relevant data for their use cases.