Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics for pharmacy trends
    How Data Analytics Is Tracking Trends in the Pharmacy Industry
    5 Min Read
    car expense data analytics
    Data Analytics for Smarter Vehicle Expense Management
    10 Min Read
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: To Our Data Perfectionists
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Quality > To Our Data Perfectionists
Data Quality

To Our Data Perfectionists

JimHarris
JimHarris
5 Min Read
SHARE

Had our organization but money enough, and time,
This demand for Data Perfection would be no crime.

We would sit down and think deep thoughts about all the wonderful ways,
To best model our data and processes, as slowly passes our endless days.
Freed from the Herculean Labors of Data Cleansing, we would sing the rhyme:
“The data will always be entered right, the first time, every time.”

Had our organization but money enough, and time,
This demand for Data Perfection would be no crime.

More Read

Text Analytics for Legacy BI Analysis
Man vs. Machine Contests: Forget “Level” Playing Fields
Data Variety: What It’s All About
Watson’s Linguistic Struggles
Top Financial Risks of Doing Business in the Cloud

We would sit down and think deep thoughts about all the wonderful ways,
To best model our data and processes, as slowly passes our endless days.
Freed from the Herculean Labors of Data Cleansing, we would sing the rhyme:
“The data will always be entered right, the first time, every time.”

We being exclusively Defect Prevention inclined,
Would only rubies within our perfected data find.
Executive Management would patiently wait for data that’s accurate and complete,
Since with infinite wealth and time, they would never fear the balance sheet.

Our vegetable enterprise data architecture would grow,
Vaster than empires, and more slow.

One hundred years would be spent lavishing deserved praise,
On our brilliant data model, upon which, with wonder, all would gaze.
Two hundred years to adore each and every defect prevention test,
But thirty thousand years to praise Juran, Deming, English, Kaizen, Six Sigma, and all the rest.
An age at least to praise every part of our flawless data quality methodology,
And the last age we would use to write our self-aggrandizing autobiography.

For our Corporate Data Asset deserves this Perfect State,
And we would never dare to love our data at any lower rate.

But at my back I always hear,
Time’s winged chariot hurrying near.

And if we do not address the immediate business needs,
Ignored by us while we were lost down in the data weeds.
Our beautiful enterprise data architecture shall no more be found,
After our Data Perfectionists’ long delay has run our company into the ground.

Because building a better tomorrow at the expense of ignoring today,
Has even with our very best of intentions, caused us to lose our way.
And all our quaint best practices will have turned to dust,
As burnt into ashes will be all of our business users’ trust.

Now, it is true that Zero Defects is a fine and noble goal,
For Manufacturing Quality—YES, but for Data Quality—NO.

We must aspire to a more practical approach, providing a critical business problem solving service,
Improving data quality, not for the sake of our data, but for the fitness of its business purpose.
Instead of focusing on only the bad we have done, forcing us to wear The Scarlet DQ Letter,
Let us focus on the good we are already doing, so from it we can learn how to do even better.

And especially now, while our enterprise-wide collaboration conspires,
To help us grow our Data Governance Maturity beyond just fighting fires.
Therefore, let us implement Defect Prevention wherever and whenever we can,
But also accept that Data Cleansing will always be an essential part of our plan.

Before our organization’s limited money and time are devoured,
Let us make sure that our critical business decisions are empowered.

Let us also realize that since change is the only universal constant,
Real best practices are not cast in stone, but written on parchment.
Because the business uses for our data, as well as our business itself, continues to evolve,
Our data strategy must be adaptation, allowing our dynamic business problems to be solved.

Thus, although it is true that we can never achieve Data Perfection,
We can deliver Business Insight, which always is our true direction.

___________________________________________________________________________________________________________________

This blog post was inspired by the poem To His Coy Mistress by Andrew Marvell.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

intersection of data and patient care
How Healthcare Careers Are Expanding at the Intersection of Data and Patient Care
Big Data Exclusive
dedicated servers for ai businesses
5 Reasons AI-Driven Business Need Dedicated Servers
Artificial Intelligence Exclusive News
data analytics for pharmacy trends
How Data Analytics Is Tracking Trends in the Pharmacy Industry
Analytics Big Data Exclusive
ai call centers
Using Generative AI Call Center Solutions to Improve Agent Productivity
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Delivering Quality – Where it Counts, When it Counts

5 Min Read

Has Personalized Filtering Gone Too Far?

5 Min Read

Recap of the Government Big Data Forum of 26 Jan 2011

4 Min Read

How to Use Pivot Tables to Mine Your Data

9 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?