You’ve heard the adage that if you only have a hammer, everything is a nail? It seems some companies are falling prey to that level of logic when it comes to MDM.
In a recent column, MDM expert Evan Levy shares the story of a client who had done all the due diligence for a master data management project. Honestly, it was a dream, the work they did they to prepare, a veritable checklist of How To Be Perfect. They’d worked through the business goals and objectives, identified the relevant 11 systems, and communicated both the low-hanging fruit and the high-level value of this massive integration effort.
The only problem? MDM wasn’t the right solution for solving their problem. What they really needed was a customer data mart, according to Levy.
Oh, the humanity!
Mind you, MDM could be helpful in resolving any discrepancy in the customer data stored in those 11 systems. But the client wanted to move all that data into the hub and store it there. And that’s just not what MDM is designed to do.
“Frequently, folks confuse the function and purpose of Master Data Management with Data Warehousing,” Levy writes. “I suspect the core of the problem is that when folks hear about the idea of “reference data” or a “golden record,” they have this mental picture of a single platform containing all of the data. While I can’t argue with the benefit of having all the data in one place (data warehousing has been around for more than 20 years), that’s not what MDM is about.”
It is, however, the core function of data warehouses and data marts. These old tools are still good at doing what they do — acting as a repository once you’ve integrated large amounts of data.
MDM works well with those technologies because it reconciles differences across the data, helping you achieve that ever elusive, somewhat mythical creature, “a single version of the truth.” That’s especially useful if you want to make sure you’re not storing six slightly different versions of “Rob,” “Robert” and “Bob” Smith’s address. As Levy notes, MDM solves one of the biggest problems of data integration, which is dealing with the complexity of reconciling and tracking single individuals (or products) across multiple systems.
In other words, MDM is more like a level than a hammer — a really nifty level that also makes sure all your 4x4s are actually 4x4s.
Of course, that simile oversimplifies, because MDM hubs do store data. Levy’s piece does a great job of explaining why the function is different from a customer data mart. He also explains why, really, we are probably just stuck with data storage silos but that tools like MDM can help organizations achieve organization despite the silos.
“If you consider recent advances with big data, cloud computing, and SaaS, it becomes even more apparent that storing all of a company’s subject area data in a single place isn’t practical,” he writes. “That’s one of the reasons that most companies have numerous data marts and operational applications integrating and loading their own data to support their highly diverse and unique business needs. An MDM hub is focused on tracking specific subject area details across multiple systems to allow anyone to find, gather, and integrate the data they need from any system.”
Levy is discussing a customer data use cases, but this same situation also happens with product data. In fact, Paige Roberts, Actian technology adoption manager for Big Data, makes a strong argument for why the integration of product data involves even more complexities than customer data.
That’s why there’s such a clear return on investment for MDM in manufacturing and other businesses — including health care — where you need to know that this 3/8 inch screw is exactly like that 3/8 inch screw.