Hi #advice-data-governance, curious to hear about how Data Products are represented in your environments. For example, • Do you capture Data Products as Glossary Terms, abstracted from its physical implementation? • Or do you capture them as Datasets? • Or do you create your own Dataset Types or Glossary types?

Hi @eager-australia-69729 What do you mean by Data Products in this case? For instance, would BI Dashboards, Materialized Views, or even DataHub itself be a Data Product?

@eager-australia-69729 if you refer Data Products in Data Mesh sense, it is closer to a dataset than a glossary term. Datahub will have different type of metadata entity model. If your “data product” doesn’t fit the existing metadata entity model, you can create a new one (https://datahubproject.io/docs/metadata-modeling/extending-the-metadata-model)

hi @acceptable-potato-35922 and @modern-artist-55754 i guess definition of a Data Product can be different from one organization to another. looking at the DataHub Features documentation, it wasn't clear to me where Data Products are meant to fit. i'm referring to the note in DataHub Features Overview (please see screenshot), and it implies that Data Products are types of entities, but am wondering if that's the most efficient approach and whether the community has been trying out different approaches. i later found this thread where @ambitious-piano-33685 suggested starting with the Glossary to represent a Data Product

I get your point, you can define a data product as a group of entities.

Got it. We haven’t done it in DataHub yet, but in the past I’ve done it (with other catalogs) as Domains. I felt like it was a nice logical separation