Semprini

One must occasionally rant. And when that cathartic wave has crashed and some of the built up cynicism washed away, hopefully the receding waters leave a perspective for a pragmatic path forward.

Enterprise architectures should represent the very best of what we can and should strive for, encourage the business and staff to reach higher and push us to see beyond the boundaries and limitations of the current landscape. I guess what it comes down to is that there's good IT and bad IT and we have become overwhelmed by a sales machine - both internal and external, which advertises one but actually delivers the other. Its not a matter of subscribing to the latest method, programme or ethos - it's about understanding the subtle idiosyncrasies and the sympathetic treatment of people, process and technology. Leaning into the complex problems, and sometimes having the courage and integrity to defend work which doesn't have an immediate payoff.

Having systems of record is a widely accepted architectural pattern used to provide clear delineation of responsibilities and guidance to end-to-end solution architectures.

It is an architectural pattern of it's time, suited to an IT landscape of large monolithic applications and was the dominant strategy since the 90s across almost all corporate IT. If this it your IT strategy, you have good governance and patterns for change and an integration architecture which is for keeping these monoliths in-sync then go forth and prosper - you will have mature IT and a reasonable cadence of change.

More likely however, is that significant data is created in what is considered systems of record, half migrated new systems of record plus micro-services and analytic / machine learning flows so the misalignment of systems of record to the business view has become more obvious and material.

There is not a good semantic fit between an applications view of data and the business view of data so lets stop pretending.

The convergence of operational, reporting and analytic data is accelerating. Polyglot persistence in combination with Data Mesh concepts deliver a simpler, more accurate and semantically consistent view of the whole data landscape.