A good thing happened today in that a webinar I was part on the subject of capture at one point turned into a discussion about data quality. From the perspective of industry best-practices, this topical pivot was not only appropriate but inevitable. But it came as a happy surprise because, in my experience, the two disciplines all too rarely get mentioned in the same conversation.
Capture and data quality both are aimed at creating a storehouse of clean, reliable, readily findable information for organizations to leverage as they earn their daily bread. But where the former tends to be handled by “content managers” – whatever those are – the latter is usually the responsibility of database administrators. As a result, the twain hardly ever actually meet, and their individual technology initiatives rarely cross over.
This is a real shame and a major leak of system value considering that, say, the data being captured off of forms, invoices, photos of dinner receipts, etc. are being piped more or less directly into one data store or another. So why approach them as wholly separate theaters of operation?
If nothing else, remember that the practice of developing, unifying, and/or standardizing on an established set of classification criteria is fundamentally the same thing as engaging in data cleansing, validation, and fusion. Both are centered on establishing a validated and efficient “truth set” against which all new information can be compared and qualified, and both are essential to boosting the speed, efficiency, and accuracy of all your business processes. Their intersection and overlap is therefore, yes, inevitable.
Want to learn more about the ever-deepening relationship between capture and data management? Care to be certified as an information professional who knows how these pieces fit in with the so many others? Need some outside perspective on your internal operations so you can move forward in as streamlined as possible? Ask about my professional training and custom consulting capabilities!