The Data Roundtable

After writing more than one hundred posts on this site about data quality, management, governance, and transformation, I’ll be periodically turning the reins over to a new friend of mine.

And, without further ado, allow me to introduce Dator.

As I’ve noted in my last two posts, I’m coming off the sidelines and stating, in no uncertain terms, my support for data quality professional certification.  In this post, I’m providing some unsolicited advice to those offering these programs.  The “short version” is “follow sound DQ practice in improving certification.”

I transitioned into a data management career as a result of my developing algorithms and developing software for data matching and cleansing. At that time, I was working on what today would be called a master data integration project, and found that nagging data quality issues such as incorrectly spelled names and changed addresses were affecting the ability to uniquely identify customer records. As a result, I started developing some ideas about data validation in the context of multiple data sources, much of which resulted in describing directives and rules about record linkage and merging records together.

At a DataFlux IDEAS conference a year or two ago during a keynote speech, Jill Dyché mentioned that many data stewards often behaved like “roving linebackers without authority” within their organization, and – to this day – I still love the analogy, more so for the “Roving Linebacker” part than the “without authority” part, of course. Ms. Dyché discusses this topic in detail in her Customer Data Integration book which should be required reading for any and all DataGeeks out there.  

In my last blog I wrote about coming into a new environment and facing the fact that things may not be designed and implemented exactly the way you would have done the implementation.  I guess when people say, “We are making friends and influencing people,” it really is true.  It is extremely important that you don’t upset the apple cart (immediately), and tactfully ease you way into that environment.

There is a tool that is more powerful than the fastest profiler, the richest dashboard and the slickest cleansing algorithms. This tool can be used by C-level execs through to the workforce on the ground.

What’s more, it’s entirely free, available in all regions and when used correctly becomes the key difference to securing rapid and long-term data quality success.

The tool is called communication, and it’s the most important weapon you can add to your data quality arsenal.

On her popular blog, my friend Jill Dyché recently wrote about Big Data Governance. From the post:

Often clients explain that they need to treat transaction data differently than they need to treat, say, customer master data. Fewer business rules, more history, that kind of thing.  That’s when we start the work of classifying different…

In my last post I outlined my reasons for sitting on the sidelines regarding data quality professional certification.  But I’m throwing my full support behind two programs, those of the IAIDQ and eLearningCurve.  (Note:  I also clarified my close ties to both in that post.  Here’s the link).