Data Science

We deal with trade-offs all the time. “You can have it good, fast or cheap... pick any two.” The implementation constraints for this decision tree are clear-cut and obvious. If you want it good and fast, it won't be cheap. If you want it fast and cheap, it won't be good. If you want it good and cheap, it won't be fast. Continue Reading →

Big Data and Data Science are overused catch phrases that can mean anything anyone wants them to mean. But the hype doesn't change the facts. We are being overwhelmed with data, here's what to do with it. Continue Reading →

Millennials empirically know that bar crawling is for recreation – not for archaic, time-wasting, low-percentage mating rituals.  If you want to meet someone, there are any number of big dating sites and apps available. Continue Reading →

In a perfect world, you just hire a bunch of data scientists, have them deploy clever algorithms, and the machine will output a clear path to higher sales, better ROI and world peace. Sadly, that’s not how it works.  Continue Reading →