One of the most common questions I get asked by our members on Data Quality Pro is, “Can you do more articles on data quality dimensions?” Part of the reason for this request is when people first start getting involved with data quality, they invariably buy data quality books and
Jim Harris recently penned an interesting article describing what happens to data quality at the top of the bell curve. The central theme of the article explains how, as we strive for greater levels of quality, we hit diminishing returns. For example, the cost of sending an engineer down a
Getting buy-in for data quality can be a real challenge, and a big part of the problem is the language barrier. If you’re on the data quality side, the financial and strategic terminology used by management may seem alien to you. Similarly, there is probably nothing more confusing to a
Over the holidays I had a chance to settle down to the usual array of Christmas movies and, as ever, Star Trek made an appearance. Now, I’m no Trekkie. But anyone with even a casual interest in Star Trek over the ages will be aware of the prime directive. This
I have previously blogged about sneezing to unleash the data quality ideavirus, but in this post I have a different kind of sneezing in mind and, unfortunately, in nose. The common cold is so-called because it’s the most common human infectious disease. Despite the apparent irony of my traditional spring and summer
In my previous post, I outlined the main components needed for a phased approach to MDM. Now, let's talk about some of the other issues around approaching MDM: data governance and the move to enterprise MDM. Where does governance come in? Throughout your MDM program, it's important that deep expertise
The "Internet of Things" is the latest buzzword characterizing the machine-generated big data that has outstripped our ability to derive value from it. Think of UPS delivering 16 million packages every day through various hubs and all the logistics and decisioning that goes into that. But how does an organization
I want to create a new series on The Data Roundtable that focuses on providing practical tips for improving data quality. Consistency is a key dimension often referred to in data quality practitioner circles. This refers to a rule where data must be consistent between two locations. For example, if
For decades, data quality experts have been telling us poor quality is bad for our data, bad for our decisions, bad for our business and just plain all around bad, bad, bad – did I already mention it’s bad? So why does poor data quality continue to exist and persist?
We’re in the process of trying to find a builder to complete an extension on our home. My "project" is five years overdue, behind budget and struggling with supplier issues. What is interesting is that every builder we interview for the new build brings his own frame of reference to the
