Data Mesh Principles

There are four distinct principles when it comes to implementing DataMesh, as follows:

1. Domain-driven ownership 2. Data-as-a-product

 3.  Self-serve data platform

4. Federated computational governance Let us discuss each of these areas in detail.

Domain-driven Ownership

As per the domain-driven ownership principle, the domain teams are owners of their respective data. For example, there can be different teams, like sales, human resources, information technology, and so on, in an enterprise. Each of these teams will generate, store, process, govern, and share their data. The ownership of the data will remain within the domain boundary. In other words, data is organized per domain. We get the following benefits by adopting this principle:

•    The data is owned by domain experts who understand the data well.

This process enhances the quality of data and the way it is stored,used, and shared.

•    The data structure is modeled as per the needs of the domain. So, the data schema is realistic.

Data gets decentralized when it is being managed by the corresponding domain.

This ensures better scalability and flexibility when it comes to management of data.

Data-as-a-Product

Data are often treated as a byproduct for the application. As a result, data are kept in silos, not stored properly, not utilized to the fullest, and thus the collaboration and sharing of the data is limited. However, when the data are treated as a product, they are treated at par with the application and are exposed for consumption to other teams and parties as a product. This process increases the data quality and makes data management efficient. A consumer-centric approach is followed that ensures that the data produced are consumable by the end consumers. This helps in maintaining well-defined data contracts that clearly define how the data will be accessed, shared, consumed, and integrated by other consumers in the enterprise. This makes the data teams autonomous, resulting in the team producing the data being responsible for that data and exposing it as a product.