For those who don’t want to click from page to page, here are all five articles in the Data Chasm series. In it, we explore the question of why we continue to see overwhelming numbers of analytics, artificial intelligence, machine Read more
Relating the challenge of launching a new corporate process to a flywheel is a tired, overused metaphor. Probably because it so often applies. Like here. It’s been hard getting started. Probably several false starts. Progress has been agonizingly slow. But Read more
I mentioned in my Christmas article that it would be interesting to see what ChatGPT would come up with for the 12 days of a data focused Christmas. We’ve been snowed in here the past couple days, so I thought Read more
If you’re just joining, welcome. Before launching in at the middle, it might be useful to go back and read Part 1, Part 2, and Part 3. I’ll wait. Recapping very briefly: It seems that most everybody has become comfortable Read more
This tale may sound familiar to companies that have not yet crossed the Data Chasm (and maybe even to some that have). A project team was modernizing a major operational system. One that had been written decades earlier. One where Read more
It all seems so easy. Companies are recognizing that the accuracy of artificial intelligence and machine learning applications is directly related to the quality of the data used to train the models. Obviously, you want to improve the quality of Read more
With Christmas approaching, I thought it would be fun to imagine what a data person might want to receive on the twelve days of Christmas. Probably not drummers drumming and calling birds (or colley birds…argue that one amongst yourselves). I Read more
This is the first in a series of articles that explores the question of why we continue to see overwhelming numbers of analytics, artificial intelligence, machine learning, information management, and data warehouse project failures despite the equally overwhelming availability of Read more