How often do your data and analytics and software engineering teams meet to align on architecture? Is this something you’d only do to prepare for a major change, or does it happen regularly?

Many organisations have the data and technology as being in the same team or have the same reporting lines. Extremely close alignment is critical for the success of the organisation.

Frequent syncs between data & engineering are crucial—not just for big changes but to prevent “compliance drift,” where sensitive data access can slip out of alignment. In my organisation we utilize AI-driven tools, in order to minimize manual checks, cut approval delays, and keep data accessible yet secure

There are two aspects here.

1. Analytics Platform --> A set of capabilities made available in self service manner to organizational resources based on persona as per organizations's standards and approved patterns.

2. Analytics Apps & Data Engineering pipelines --> These are initiative specific and will leverage the analytics platform to meet the business outcomes.

The engagement with architecture on these 2 can happen at different frequency.

For analytics platform, there will be architecture engagement anytime new features are added to the platform and major changes such as technology swap etc. This is to ensure platform aligns to the non functional requirements and align to enterprise standards & patterns.

For initiatives, there will be architecture engagement at the inception to ensure implementation architecture aligns with enterprise guidelines and right interface rationalization (integration types) is happening to deliver the business outcomes.

I'd expect a review to happen quarterly or at least 2x a year.
I phrase as a "review" because there will likely be some minor changes, but if your meeting multiple times a year to discuss how your architecture (core infrastructure, patterns, paradigms, implementation) is changing, I would worry that your team is spending far too much time playing with new or unknown tech.

Your architecture shouldn't be shifting wildly so often to necessitate meetings or education multiple times a year.

Review and alignment on the current state and direction are good.

Data is the foundation for digital transformation in today's AI era. Organizations in the digital leader category generally have their data and analytics and software engineering teams align on architecture regularly, ensuring cohesiveness and adaptability throughout the SDLC, whether it follows a hybrid, waterfall, or agile approach. We typically meet on a weekly or biweekly basis, depending on the project’s lifecycle and complexity. This consistent cadence helps maintain continuity, quickly spot deviations from architectural discussions and designs, and address issues early. The objective is to maintain flexibility through architectural reviews and data checkpoints, enabling teams to recalibrate or innovate collaboratively before any major platform or application changes.