Now that we have determined that MDM, Data Governance, Data Cleansing and Data Quality are important as well as the new trend for blogging, tweeting and discussion in general, I ask the most important question . . . HOW?  When do we get to the discussions on the content?

I am a very detail oriented person; I have to be as one of my largest accounts requires me to participate in the day to day deployment of global MDM processes for one the largest automotive manufacturers! I am very interested to learn how businesses in other industries manage their data. I would hope that sharing of information and best practices among industry partners will be a win-win situation. At a minimum the discussion will be refreshing; the sharing of innovative information the will spawn the creative improvement needed to create truly efficient knowledge driven business processes, data classifications, metadata and definitions and translation. . . is anyone interested in discussing the logistics of managing translation as part of Master Data Management?

Is anyone interested in discussing my struggles and sharing yours trying to find standard global translations for ISO UOM (Unit of Measures)?

Is anyone interested in discussing what fields should be included in a MDM Data Governance Program for MRO data; UNSPSC, warranty, term of warranty, lead time, estimated price, ECCN, etc.

What Schema or classification structures are you using for spare parts and maintenance items? What about a discussion on using a public vs. priority classification system?

What are some best practices for migrating, profiling, structuring, mismatching and re-verifying legacy system data?

We have a nifty data mismatch process for manufacturer contact information; will this be easily implemented for a CRM data project? What about patient contact information in the healthcare industry?

There are a few bloggers out there that continually add content to their writings but it is starting to appear to be a small group, anyone out there interested in achieving data quality want to discuss “real” life best practices, lesson learned or discuss HOW of MDM, data quality or data cleansing.