by Angela Guess
In a recent interview Daniel Teachey shared his insights on the challenges that unstructured data present to data governance. He said, “In the last year or so, governance of unstructured data has probably been the highest-growth area in governance. Let’s take a financial example. Look at something that’s, shall we say, quasi-structured, such as a financial trade between a buyer and seller on the stock market, or a transfer of money between international banks. These typically involve very specialized unstructured or semi-structured documents or files. They are being exchanged back and forth, and they need to include elements that can be used by data quality technology to manage them — to understand that the routing number here is equal to the routing number there, or that the intended target bank is [correct].â€
Teachey continued, “The issue with unstructured and semi-structured data is the extent to which a technology can locate the pieces of information they need, understand what they have, and then have that represented within a governance technology structure. The systems need to be able to flag problems and alert compliance officers, for example, even if we’re talking about an XML document that really isn’t structured like a database or an application. There are triggers you can look for, such as routing numbers. The technology needs to be as smart as the different types of data it’s being forced to handle.â€
photo credit: blprnt_van
