JUL 13, 2012 11:27am ET

Related Links

Early Retail Adopters Moving to Full-Scale Indoor Location Technology Deployments
April 16, 2014
Modifying Foreign Key Definitions
April 14, 2014
Insurers' IT Spending Continues to Grow
April 13, 2014

Web Seminars

April 29: Create a data protection strategy with open, software-defined storage
April 29, 2014
New Best Practices To Manage Customer Information
May 7, 2014
May 13: Cost-effective, scale-out backup in 1 solution
May 13, 2014
blog

Philosophical About Perfect Data

Print
Reprints
Email

Good thoughts and responses to last week’s column on Living With Imperfect Data, which postulated, “Sometimes it’s better to have everyone agreeing on numbers that aren’t entirely accurate than having everyone off doing their own numbers.”

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 (3)
Certainly, Sales, Operations, Product, and even the customer look at things in different ways simply because each different way of looking happens within a particular context of a particular process or function. But when multiple versions of the truth pop up within the same context, there is a problem. Additionally, problems arise when truth is asserted without context.

Still, a certain single truth remains: Underlying all the varying enterprise contexts, processes, and functions is but one foundational, holistic, naturally and fully integrated enterprise structure. Mess up that truth to a great extent with disparate "silo" data solutions, then the thinking that "as long as the data are good enough to make sound decisions ..." merely rings as a rationale for inaction to do better to improve data quality and to do it continually.

Posted by Ed J | Monday, July 16 2012 at 1:26PM ET
Jim's article shows quite well that new categories of data occur and that new rules need to be defined. Imperfect data required: Decisions are already taken when selecting the data we track, when selecting data and data structures for reports and not to forget when defining the decision fields itself. Just repeating the well-known following story: A drunk loses the keys to his house and is looking for them under a lamppost. A policeman comes over and asks what he's doing. "I'm looking for my keys" he says. The policeman states: "But there are definitely no keys here around". The drunk: "But searching with light is so much better". A free translation into Jim's topic: The more decisions extend into the future the less reports on structured 'accurate' data are really helpful. Two examples: To improve business processes it makes sense to check the free text communication of bookers, planners, dispatchers, invoice operators. To get a feeling of consumer markets the collection of customer pain points in blogs etc. is most useful. There are a lot of similar examples to get an idea about the health of suppliers or VIP customers. Rules for imperfect data required: The use of data has always a 'legal' dimension. As Jim said you cannot always wait for all data covering a decision. A decision has an optimal time window to be taken, too early or in our case too late the additional costs can be tremendous. But if based on existing structured data these data should be accurate. Other rules need to be defined to treat and use unstructured data, Big Data, or other by nature imperfect data.
Posted by Peter K | Monday, July 16 2012 at 2:30PM 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.

Are you actively evaluating master data management technologies and their ability to scale and support emerging trends around big data, social and mobile?

Yes 61%
No 23%
Don't Know 9%
Not Applicable 6%

 

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.