Every one of us knows how important data management really is. However, being simply aware of the benefits of MDM and understanding its importance, isn't sufficient enough to implement an MDM tool successfully. One of the most crucial problems, when it comes to data management implementation, is the inability to source quality data. Sourcing information is a vital element of the master data management process, as the entire system revolves solely around it. If we are unable to identify the right sources of quality data, then all the other factors of data management like data transformation, standardization, normalization and its analysis will be affected.
The right method of implementing master data management is to think big, but start small. At first, one should start with a small set of data source, and then increase with time. The moment we identify the right source with proper entities and dependable attributes and domains, half the battle towards quality data governance is won. After finding the correct data source, you will be able to create a strategy to cleanse the derived data, build relevant and efficient standardization engines and create rules, that aid in assembling the right set of data. Alternately, you can rely on a technology partner to bring in domain expertise for standardization and cleansing.
Continue Reading...
0 comments:
Post a Comment