A data mesh is a set of read-only products made of data that are general purpose relative to not being designed to answer a specific question or set of questions. For sharing the data on the outside for a domain in a way others can consume that data. But each data product is designed specifically for data consumption/analytics. And the overall mesh setup, whether at the data product or data platform level, works to make data products interoperable so you can combine data from multiple domains.
There are many additional aspects of a data mesh but just following the pillars* themselves does not necessarily mean you will create a data mesh. For example, many are following the pillars in creating their ML models or an event mesh. The data mesh itself is the set of read-only data products made of data – each data product is a node on the mesh.
* The four data mesh pillars are:
1. Domain ownership of data and how it is stored/served
2. Data as a product
3. Self-serve data infrastructure
4. Federated computational governance