Tag Archives: data model
Several years ago I had the fortunate opportunity to participate in a post-mortem study of a $100 million dollar project failure. No one likes to be associated with a project failure, but in this case it was fortunate since the size of the write-off was large enough that it forced the team to take a very hard look at root causes and not just do a cursory analysis. As a result we finally got to the heart of a challenge that has been plaguing data architects and designers for 20 years – how to effectively use canonical data models. (more…)
The current hot topic in the MDM space is multidomain master data management. And rightly so, as multidomain MDM has the potential to drive far more value for companies than limited single-domain MDM initiatives (aka CDI, PIM) that focus on a specific class of data such as customer or product.
We’ve heard interesting discussions that multidomain MDM is just about storing the multiple domains within the data model. That is a major misinterpretation. While it’s certainly true that you need to have a data model that’s flexible enough to accommodate multiple data domains (e.g. product, customer, supplier), the data model itself is not the be-all and end-all of multidomain MDM. It’s a requisite starting point, sure, but you need to be able to do so much more. For instance, the ability to match and merge data across various domains is extremely important. Same goes for data cleansing.
Think of it this way: you’re using a dedicated PIM system. It does a great job of matching data fields in ways that are very valuable in addressing problems with product-centric aspects of your business: supply chain, inventory management, etc. Can this system do a good job matching and merging data fields from multiple domains? Can it provide the kind of data cleansing capabilities you’d need if you wanted to incorporate customer data?
A true multidomain MDM hub will provide out-of-the-box capability to:
- model any data domains
- cleanse, correct, standardize, and enrich all types of data
- match the different types of data and merge them into a single source of truth
- relate across the different types data: customer-to-product, vendor-to-material, contact-to-organization, employee-to-location, etc.
To top it all, the data governance application should support the creation, consumption, management, and monitoring of all these types of data.
So to realize the promised value of multidomain MDM, you’ll need a proven multidomain MDM hub and a data governance application that supports all these capabilities.