OCDQ Blog
AUG 21, 2012 9:13am ET

Related Links

Health Information Exchange Requires Nationwide Patient Data Matching Strategy
August 14, 2014
Analytics CEO Schools Payers at AHIP
June 16, 2014
Making Sound Business Decisions
June 11, 2014

Web Seminars

Why Data Virtualization Can Save the Data Warehouse
September 17, 2014
Essential Guide to Using Data Virtualization for Big Data Analytics
September 24, 2014
blog

Relationship Advice for Data Quality

Print
Reprints
Email

In his recent Information Management column, Malcolm Chisholm wrote that data quality is not fitness for use as it is most commonly defined, stating he thinks “a strong case can be made that the definition is indeed inappropriate and should be replaced with a better one.”

Get access to this article and thousands more...

All Information Management articles are archived after 7 days. REGISTER NOW for unlimited access to all recently archived articles, as well as thousands of searchable stories. Registered Members also gain access to:

  • Full access to information-management.com including all searchable archived content
  • Exclusive E-Newsletters delivering the latest headlines to your inbox
  • Access to White Papers, Web Seminars, and Blog Discussions
  • Discounts to upcoming conferences & events
  • Uninterrupted access to all sponsored content, and MORE!

Already Registered?

Advertisement

Comments (4)
Why do we need a definition for data quality? Consider this thought from Sir Karl R. Popper from Martin J. Eppler:

"I do not say that definitions may not have a role to play in connection with certain problems, but I do say it is for most problems quite irrelevant whether a term can be defined (or not). All that is necessary is that we make ourselves understood."

While data may seem readily definable, I increasingly concur with Robert Pirsig that quality is not. He believes: "everyone knows what it is but no one can define it."

Posted by Peter P | Wednesday, August 22 2012 at 11:29AM ET
In all my many long years in IT (evienced by the receding hair line and the greying of what is left) I have been passionate and still am passionate about the data AND its meaning.

How about using the terms "syntactic DQ" for what is now commonly referred as DQ (with emphasis on "fitness for use") and "semantic DQ" (for when the data has precise meaning/semantics)?

Surely, when the data has high "semantic DQ", use by the Interpretants wont be wrong.

- Madani B (Sydney)

Posted by Madani B | Wednesday, August 22 2012 at 11:17PM ET
Add Your Comments:
You must be registered to post a comment.
Not Registered?
You must be registered to post a comment. Click here to register.
Already registered? Log in here
Please note you must now log in with your email address and password.
Twitter
Facebook
LinkedIn
Login  |  My Account  |  White Papers  |  Web Seminars  |  Events |  Newsletters |  eBooks
FOLLOW US
Please note you must now log in with your email address and password.