David Binkley, Senior Technical Account Manager, Harte-Hanks Trillium Software
A whisperer is a person who is able to tame or control animals, especially by talking to them in gentle tones, e.g. a horse whisperer.
David Binkley, Senior Technical Account Manager, Harte-Hanks Trillium Software
A whisperer is a person who is able to tame or control animals, especially by talking to them in gentle tones, e.g. a horse whisperer.
There are people who make a living out of “talking” to data to turn it into useful information. They perform many functions ranging from statistical analysis to accounting, customer support, sales, and marketing. Without them, most companies and organizations would quickly grind to a halt. As data volumes expand, these people will be even more important in business and government.
A small group of those people refer to themselves as “Data Whisperers,” and in some ways I agree with that usage. I’m more likely, however, to argue that data “whispering” should be done by data stewards well before it is compiled into useful information. From a user’s perspective, isn’t all data “wild” before it’s captured in our applications and we “tame” it so it can be effectively used? If so, aren’t those “taming” techniques and tools actually data quality related?
Isn’t it also within our data quality mandates to “talk” to the data a gentle manner to improve it and not treat it so badly that it works against us instead of for us? We’ve always needed to be gentle with data (do no harm) and to use state-of-the-art data quality software to effectively “talk” to the data so that corrections can be made before it reaches downstream applications. If you aren’t already treating your data gently, ask yourself how successful will you be in the long term if you continue to force “wild” data into your data structures?
I run into both “whispered” and “un-whispered” data implementations all the time, and there’s no question that I see better results in companies that treat their data well using “whispering” techniques as performed using data cleansing, discovery, management, monitoring, profiling, and standardization software. But, in reality, many times in your career you will encounter untamed, badly treated data. To be successful with it, you need to approach the opportunity calmly (and treating its users the same way), while talking to the data with the right tools to create meaningful information for use in critical business applications. When you are successful in doing this, you can rightfully be considered a true Data Whisperer.
A Data Whisperer is a person who is able to tame and control wild data, using the appropriate tools and techniques to turn it into useful information for business success. Is that you?
Keep these two pictures in mind:
Un-whispered data applications are usually stressed.
While whispered data applications are calm and collected.
