This Sunday is February 14—Valentine's Day—the annual celebration of enduring romance, where true love is publicly judged according to your willingness to purchase chocolate, roses, and extremely expensive jewelry, and privately judged in ways that nobody (and please, trust me when I say nobody) wants to see you post on Twitter, Facebook, Flickr, YouTube, or your blog.
Valentine's Day is for people in love to celebrate their love privately in whatever way works best for them.
Valentine's Day is not for data.
However, when was the last time you showed your data how much you care?
Data needs love too.
Sometimes, I am sure that you feel you've got to run away, you've got to get away from the pain that poor data quality has driven into the heart of your organization.
The data you share throughout the enterprise seems to have lost its light, for you toss and turn, you can't sleep at night.
Once you ran to data—you ran—now you run from data—this tainted data you've been given.
You feel you've given data all a person could give. It's taken your tears and that's not nearly all.
Oh, tainted data—tainted data.
You really want IT (if you're with the Business) or the Business (if you're with IT) to make things right.
And you think data quality just needs a one-time cleansing project for someone else to play.
But I'm sorry, data quality doesn't play that way.
Don't ignore data, please. It cannot stand the way you tease. Data loves you though you hurt it so.
Data doesn't want to pack its things and go.
It's not your data, it's you
The majority of data quality initiatives are reactive projects launched in the aftermath of an event when poor data quality negatively impacted decision-critical information.
Many of these projects end in failure. Some fail because of lofty expectations or unmanaged scope creep. Most fail because they are based on the flawed perspective that data quality problems can be permanently “fixed” by a one-time project as opposed to needing a sustained program.
Tactical initiatives will often have a necessarily narrow focus. Reactive data quality projects are sometimes driven by a business triage for the most critical data problems requiring near-term prioritization that simply can't wait for the effects that would be caused by implementing a proactive strategic initiative (i.e., one that may have prevented the problems from happening).
Even when a reactive data quality project is successful, it's success will only be short-lived.
Another project will be necessary when the organization is forced into triage once again during the next inevitable crisis where poor data quality negatively impacts decision-critical information.
One reactive project at a time will never do data quality right—because one is the loneliness number that you'll ever do.
Maybe you're just not that into your data?
Across the vast digital landscape of the Internet, I see you rolling your eyes because you know what's coming next—the talk.
That's right—it's time to talk about your relationship with data, about your need to take responsibility for data quality.
I see you hesitate. After all, nobody has a data governance ring on their finger, do they?
Data governance establishes policies and procedures to align people throughout the organization. Successful data quality initiatives require the Business and IT to forge an ongoing and iterative collaboration.
Neither the Business nor IT alone has all of the necessary knowledge and resources required to achieve data quality success.
The Business usually owns the data and understands its meaning and use in the day-to-day operation of the enterprise and IT usually owns the hardware and software infrastructure of the enterprise's technical architecture.
The Business and IT must partner together to define the necessary data quality standards and processes.
But maybe you previously attempted a data governance program or other initiative requiring Business-IT collaboration.
Perhaps harsh words were spoken, promises were broken, old wounds were opened, and collaboration walked out that door.
Are you too proud to make up? Are you ready to break up?
Or maybe you're just not that into your data?
I don't know much
Look at your data, I know its poor quality is showing. Look at your organization, you don't know where it's going.
So many questions still left unanswered, so much that's never broken through.
But the Business and IT were made for each other. Just like Data Governance and Data Quality were made for each other.
Just like you and your data were made for each other.
I don't know much, but I know data needs love too. And that may be all I need to know.
I had to say I Love Data Quality in a Blog Post
Well, I know it was kind of strange. I hope it made some sense to you. But what I had to say couldn't wait.
I know you will understand. Every time I tried to tell you, the words just came out wrong.
So, I had to say I love data quality in a blog post.
Maybe every time the time was right for you to start your data governance program, all your words just came out wrong.
Maybe you'll have to say you love data quality and you need a data governance program using this blog post?
Happy Valentine's Day to you and yours.
Happy Data Governance and Data Quality to you and your data.