by Angela Guess
A recent article examines best practices for identifying the right sources for master data. It begins, “Among several challenges faced when we kick start an MDM implementation is the step to determine which source to consider for initial phase of deployment. Amidst all crucial aspects such as data collection, data transformation, normalization, standardization, matching etc, this step of source identification is critical factor for realizing MDM benefits early on. The proven process to implement MDM is to start with small set of data sources and grow incrementally. Once we identify the sources having correct entities, dependent domains and attributes, we can do an effective ground work for (1) Creating broad set of rules to cleanse the data, (2) Building standardization engines applicable to all relevant data entities and (3) Constructing rules to identify suspects so as to create single version of truth.”
It continues, “Getting things straight at the beginning is critical aspect of the MDM project as it acts as a foundation for future source system integration plans. This also allows us to accomplish easier enterprise wide MDM roll out by adding additional sources of data to MDM hub. So, the question is how to choose the sources which will get into MDM during this inaugural phase considering the organizations will have huge application landscape and will not know which systems are responsible for which master data. This is also a very revealing act for many of customer representatives themselves when they find dozens of databases containing data which they did not know existed.”
photo credit: aussiegall
