New use cases for MDM have moved far beyond the basic master product or customer data.
Master data management (MDM) isn’t what it used to be. It’s so much more, according to Forrester Analyst Michele Goetz, who wrote about it in a 2014 first quarter report, “The Forrester Wave™: Master Data Management Solutions.”
“Prior to 2011, MDM helped enterprises solve challenges pertaining to data quality and data integration that manifested as duplicate records in application systems and data warehouses,” Goetz writes.
At that time, it was basically a way to purge excess or defective data from customer or product data, depending on its heritage. It couldn’t really handle scale, complex relationships or hierarchies, she added. Then came Big Data, with new challenges related to “hyper-federated data landscapes,” as she calls it. Vendors adapted quickly.
“New releases of MDM technology emphasized data modeling, data linkage, and master profile orchestration over data integration, cleansing, and the golden record,” she states. “Today, organizations face an altered vendor landscape.”
Not surprisingly, this has led to use cases beyond the basic “master product or customer data.” Here are two uses I’ve seen highlighted recently:
Householding: Householding is the practice of grouping like data from multiple sources, and it’s not new. Back in the day, it was accomplished by ETL. Now householding is “one of the most prominent aspects of selling by many industries today,” according to MDMGeek.com blogger, Prashant Chan, a technical solution architect specializing in multiple MDM and data quality tools.
In that use, the goal is to link or group all the data about a specific person or household across multiple sources.
“What house holding information allows is the ability to find out the aggregated relationship of a family as a whole with the organization,” Chan writes. “For example, a retailer may want to group customers from the same family unit to reduce cost of marketing and also cater to the preferences of the household versus individual customer preferences.”
Even with MDM, householding comes with unique challenges, Chan writes. For instance, you have to figure out how the information is derived.
