Semprini

BI & analytics loves Data Autonomy and event driven architecture. In the operational side of Semantic Hub / Data Mesh, data is already clean and in business form. Data engineering can subscribe to all significant business object changes and metrics can be automatically calculated live. Dimensional modelling also becomes a much simpler process as canonical data is available near real time.

The data engineering and integration teams can become an active part of data governance and data stewardship. Working closely with the business domain SMEs, everyone is on the same page and reporting is simplified.

Data Autonomy is a collaboration of A Holistic Data Fabric/Mesh, RESTful interfaces, RESTful events and enterprise micro-services. Focused around Resource Oriented Architecture (ROA) rather than Service Oriented Architecture (SOA), its purpose is to provide the ability to change rapidly by keeping the level of dependencies constant across the IT landscape.

Standard event driven integration practice is to take data from a system, transform into a middle model and then transform to each destination. Data Autonomy simply says that while we have the data in the middle form, lets save it.

Each business domain must be free to evolve and mature independently as the view of significant business objects evolves. The data governance group with data stewards and SMEs should be responsible for producing domain aligned data product definitions which are then realized into data products. The features of these data products should cover interfaces and persistence for both operational and analytical data.

If you have a "microservice" which exposes an API calling a back end system, you don't have a microservice - you have an API. Your API has wisely used some of the concepts of microservice architecture. Microservice architecture is not an integration architecture, it's an application architecture and applications are responsible for business logic. This distinction is important because the beauty of microservice architecture is both technical and behavioural.

However, I'll extend an olive branch to the API people, no doubt aghast by my blasphemy, by calling them "integration microservices".

Integration microservices are fine I guess, but too often they are used, just as integration is often used, to sweep the legacy monster under the carpet so we don't have to see it - out of sight, out of mind. We implement integration microservices containerised, auto-scaling, auto-healing etc, IT management has an orgasm, we all add something to our CVs and the legacy monster waits.

The key concept in Data Autonomy architecture is to master significant business objects away from applications. CBE is an example of a restful data platform to persist canonical / business domain data. It also shows the use of CDAF - Continuous Delivery Automation Process. The project can be found here: Github: CBE