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Data Quality: In the Eye of the Beholder?

Woman eye and light, concept background

~ by Marty Shaw, Global-Z Director of Sales & Marketing

We’re social beings, right? We like to know what other folks do and how they do it; or at least I do. Often at family gatherings like Christmas, New Years and birthday get-togethers with family and friends the question comes up worded something like this:

“So, how’s work?… What is it you do again?”

The answer to the first question is easy. Business has been good and getting better.  The second question, well, that suggests that I’ve not done a good enough job in the past explaining what Global-Z does for our clients.  My answer begins with something like “Global-Z provides expertise in international postal data quality…” Because most of my friends and family do not work in internationally focused organizations often the remaining explanation about the kinds of data quality benefits we provide for our customers appears to be received like Charlie Brown’s teacher was speaking to them.

Even for GZ News readers who do work in international businesses the phrase “data quality” and related terms can mean so many different things to so many different organizations; even different departments and different individuals within those departments.

I read a number of blogs and listen to podcasts on the topic of data quality, keeping a notebook handy to jot down something that catches my interest that I may want to borrow.  While I may not be able to attribute the following definitions to their originators, please know they are not mine, but I like them and will use them as though they are (Thank you, learned and kind anonymous masses).

Often defining “data quality” includes comparing or contrasting the words “data” and “information”.  One of GZ News’ contributors, Graham Rhind, recently defined them in a podcast I was listening to as follows: “Data is stored information; while information is perceived data.” My handy-dandy notebook also includes the unattributed definition of three important data quality terms:

Data: facts about stuff (e.g., 8024451011 is a 10-digit number)

Information: Facts about stuff in context (e.g., 802-445-1011 is a 10-digit phone number)

Knowledge: Facts about stuff in context put into action (e.g., 802-445-1011 is a 10-digit phone number which can be used to reach Global-Z’s Data Center)

How does this come down to helping define data quality? A recent OCDQ blog post on Redefining Data Quality described data quality as “fit for purpose”. This to me helps bring it home to the most important person, you, or any person using data. That is, data quality is in the eye of the beholder. What are your purposes working with the data, and what defines it being fit for your ultimate goals?  The answers can and likely will be very different if you’re a direct marketer, work at a logistics company, an insurance underwriter, or thousands of other business use cases for international address data. The podcast associated with this same OCDQ blog post added that data quality also must address two important aspects of data management; defect management and change management.  Data will hold some things in common across industries; a certain percentage of the data will be incorrect, and a certain percentage of it will change over time, necessitating that defects are corrected and changes are made current.

The debate on the definitions of data, information, data quality, and other related terms will continue. Do you agree with these definitions? How do you define these terms? Please let us know.