I have been assembling a slide deck for an upcoming TDWI web seminar on Strategic Planning and the World of Big Data, and I am finding that I might sometimes use two different terms (“data reuse” and “data repurposing,” in case you ignored the tootle of this post) interchangeably when in fact those two words could have slightly different meanings or intents. So should I be cavalier and use them as synonyms?
When I thought about it, I did see some clarity in differentiating the definitions:
- “data reuse” means taking a data asset and using more than once for the same purpose.
- “data repurposing” means taking a data asset previously used for one (or more) specific purpose(s) and using that data set four a completely different purpose. Read more
I just finished reading a very interesting book on the evolution of Prohibition in the US in the mid-late 1800s and early 1900s. The book, “Last Call” by Daniel Okrent, followed the temperance movement that started with a bunch of men pledging to stop drinking through its alignment with the women’s suffrage movement, to the passage of the Prohibition amendment, followed by its eventual repeal. One revelation to me was that , according to the author, the political processes that enabled the passage of prohibition essentially created the modern methods of political lobbying, the ability of minority parties to significantly sway majority rule, and (when push comes to shove) that when you mandate behavioral changes, you probably should have four things in mind:
- Your value proposition must be appealing enough to convince those you are trying to regulate that it is in their best interests to comply;
- You should ensure that you have adequate resources for inspection, monitoring, and enforcement;
- You don’t allow so many loopholes that enable the ad hoc creation of classes or parties who can blatantly evade compliance; and
- You don’t reward illicit behavior. Read more
Filed under: Data Governance, Data Profiling, Data Quality, Master Data
I am honored to be one of the co-moderators of the upcoming TDWI Solution Summit on Master Data, Quality, and Governance, to be held March 4-6 in Savannah, GA. I attended one of these events in the past, met a lot of people currently engaged in launching an MDM project, but this year I have helped to find some cases studies that focus on master data as a result of good data quality and governance techniques, not the driver. Please go to the web site and check it out, then apply to be a delegate! Hope to see you there!
It has been a while since I posted an entry – mostly signs of “busy-ness” in trying to wrap up projects before the end of the year. However, I did have an interesting experience recently with one of our customers, with whom we are working on developing a best practices guide for data governance.
For this customer, I was being provided with badge access to be able to get in and out of the building, and we had an appointment with security to have the badge created (as well as a bunch of other security-type things). As some of you might know, I never use my first name, but go by my middle name, David. However, since my driver’s license has my full name on it, I was told that my badge would have my real first name (“Howard”) on it, and if I needed to contact security for any reason, I would need to give them my real first name (which I *never* use). Read more
It was nice to see that Jim Harris referred to my earlier post questioning the experts’ pronouncements of the costs of poor data quality, and it triggered yet another thought about the perception of the value of data quality improvement envisioned as processes for prevention. The main idea is this: from the perspective of the individual paying for prevention, those processes are seen *only* as a cost, not a value.