Before starting a new buzzword, I think we need to revisit an old one: MDM. Master data management (MDM) is a term used for the last few decades to help with the growing challenge of having a "single view" of entities across organisations, such as customers, businesses, and products. It became more evident as organisations started to use multiple systems, maintain data in multiple places (aka silos), merge with new businesses and getting data from external sources. The evolution of big data, IoT and AI have only made that challenge of single view even bigger.
Despite the continuous proliferation of data and data management tools in the past decade, and the challenges accompanied with that, most MDM solutions and initiatives failed, and failed miserably. A few recent engagements I had with customers demonstrated how they try to avoid talking about MDM as a solution, or somehow manage to give (or ask) for different names.
In a few recent engagements I had in my current role, customers demonstrated how they try to avoid talking about MDM as a solution, or somehow manage to give (or ask) for different names for the solution, and that's due to its history in underdelivering on its promises and goals.
I can't blame them. The past 20+ years have proved that MDM solutions from "leading" global vendors were unreliable, not scalable, and simply don't do a good job- they under deliver. And surprisingly, with all sorts of advancements we've seen in many areas in data management, these solutions managed to stay unchanged, using the same methods and techniques, year after year, to tackle an ever-existing challenge.
MDM has fundamentally failed (and continues to) because it:
- Promotes the idea of "single view"
- Deals with data and data issues as a first-class citizen
- Continues to impose old techniques and rigid models to deal with data sourcing, processing, and serving.
In this 4 parts blog, I'll be covering and discuss in details each of these points.
Stay tuned!
Next: Rethinking MDM and Our Approach to It | Part 2/4: There is no such thing as a "Single View"