Data Architecture Layers Pattern with Shane Gibson

Medallion architecture has been a masterclass in vendor marketing. It has the scent of new lamps for old. A fresh name, polished diagrams, compelling colour coding.

And yet, layered data architectures themselves are not new. They have delivered real value for decades. Separating raw data from designed data from consumable data is not hype. It is a proven architecture.

The tension has never been the idea of layers, the tension has always been this:
- What data actually goes in each layer?
- What patterns are allowed in each layer?
- What governance expectations change as data moves upward?

Those arguments have played out in design reviews, architecture boards, data platform teams and governance councils for years. Data engineers debate transformations. Data stewards debate ownership and quality. Architects debate design.

After feeling this frustration for decades, I decided to try and make it slightly better.

I created the first iteration of an open source checklist. A structured, explicit way to describe the context of what each layer means in your organisation, what is allowed to happen where.

In this session, I will take you through the open source Data Architecture Layers Pattern Checklist. We will explore how it can reduce ambiguity, expose assumptions, and create a shared language between engineering and governance.

And then I will try to persuade you to help me iterate it further.