The Data Roundtable
A community of data management experts
Here on the Data Roundtable we've discussed many topics such as root-cause analysis, continual improvement and defect prevention. Every organization must focus on these disciplines to create long-term value from data quality improvement instead of some fleeting benefit. Nowhere is this more important than the need for an appropriate education strategy, both in
So much for a single version of the truth.
I have probably touched on this topic many times before: accessing the data that has been loaded into a master data environment. In recent weeks some client experiences are really highlighting something that is increasingly apparent (and should be obvious) for master data management: the need to demonstrate that it
There are multiple types of data models, and some companies choose to NOT data model purchased software applications. I view this a bit differently. I think that any purchased application is part of our enterprise, thus it is part of our enterprise data model (or that concept is part of the
When you examine where most data quality defects arise from, you soon realise that your source applications are a prime culprit. You can argue that the sales team always enter incomplete address details, or the surgeons can't remember the correct patient type codes but in my experience the majority of
Data. Our industry really loves that word, making it seem like the whole world revolves around it. We certainly enjoy revolving a lot of words around it. We put words like master, big, and meta before it, and words like management, quality, and governance after it. This spins out disciplines