Data quality is definitely not a one-time project, but instead requires a sustained program of enterprise-wide best practices that are best implemented within a data governance framework that “bakes in” defect prevention, data quality monitoring, and near real-time standardization and matching services—all ensuring high quality data is available to support daily business decisions.
However, implementing a data governance program is an evolutionary process requiring time and patience.
Baking and cooking also require time and patience. Microwavable meals can be an occasional welcome convenience, and if you are anything like me (my condolences) and you can’t bake or cook, then microwavable meals can be an absolute necessity.
Data cleansing can also be an occasional (not necessarily welcome) convenience, or a relative necessity (i.e., a “necessary evil”).
Last year on Data Quality Pro, Dylan Jones hosted a great debate on the necessity of data cleansing, which is well worth reading, especially since the over 25 (and continuing) comments it received proves it is a polarizing topic for the data quality profession.
I reheated this debate…
Data quality is definitely not a one-time project, but instead requires a sustained program of enterprise-wide best practices that are best implemented within a data governance framework that “bakes in” defect prevention, data quality monitoring, and near real-time standardization and matching services—all ensuring high quality data is available to support daily business decisions.
However, implementing a data governance program is an evolutionary process requiring time and patience.
Baking and cooking also require time and patience. Microwavable meals can be an occasional welcome convenience, and if you are anything like me (my condolences) and you can’t bake or cook, then microwavable meals can be an absolute necessity.
Data cleansing can also be an occasional (not necessarily welcome) convenience, or a relative necessity (i.e., a “necessary evil”).
Last year on Data Quality Pro, Dylan Jones hosted a great debate on the necessity of data cleansing, which is well worth reading, especially since the over 25 (and continuing) comments it received proves it is a polarizing topic for the data quality profession.
I reheated this debate (using the Data Quality Microwave, of course) earlier this year with my A Tale of Two Q’s blog post, which also received many commendable comments (but far less than Dylan’s blog post—not that I am counting or anything).
Similarly, a heated debate can be had over the health implications of the microwave. Eating too many microwavable meals is certainly not healthy, but I have many friends and family who would argue quite strongly for either side of this “food fight.”
Both of these great debates can be as deeply polarizing as Pepsi vs. Coke and Soccer vs. Football. Just for the official record, I am firmly for both Pepsi and Football—and by Football, I mean NFL Football—and firmly against both Coke and Soccer.
Just as I advocate that everyone (myself included) should learn how to cook, but still accept the eternal reality of the microwave, I definitely advocate the implementation of a data governance program, but I also accept the eternal reality of data cleansing.
However, my lawyers have advised me to report that beta testing for an actual Data Quality Microwave has not been promising.
