#canonicalmodel

Ask a room full of data professionals what data management means and you’ll get a flood of confident answers,delivered with total conviction and very little agreement. Ask the same room about Master Data Management (MDM) and the certainty evaporates. Is it a tool? A governance function? A central team? A golden record? Most organisations use the term daily, yet struggle to explain what it…

Most organizations chase AI capabilities before their data is ready for it. But AI can only reason effectively when the data it consumes is structured, harmonized, and meaningful.This article explores how combining canonical models and ontologies creates that foundation, transforming disconnected data into a unified knowledge layer that AI can truly understand and act upon. Canonical models…

Over time, I have noticed a growing confusion between Canonical Models and Ontologies. Many people see them as interchangeable, or at least overlapping, because both aim to establish a shared understanding of data across systems and teams. That confusion is understandable. Both disciplines speak about “common meaning,” “shared vocabulary,” and “data relationships.” Yet their intentions are not…

Governance frameworks establish the structure for managing data, ensuring that data assets are handled responsibly, ethically, and in compliance with relevant regulations. This approach is directly applicable to canonical models. Previous Posts in this series Canonical-model Canonical Model: Turning the Outside-In view into a Common Language Canonical Model: When data changes, so does the…

In my previous post, I introduced Canonical Models from a high-level perspective. In this post, I go further and show how this modeling approach provides real-world benefits when looking at legal entities like customers and vendors from an Outside-In perspective. Modern organizations have vast amounts of data on customers, suppliers, and markets, yet struggle to connect it in a clear and…