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.
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, and I can assure you that if you don’t know what to do with it, your competition will.
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.
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.
Data science is all the rage. Almost every CMO I know wants a data scientist for their very own – they are the status symbol du jour for senior executives everywhere. But… building the right data science team for your organization is not as easy as picking the right data scientist.
While the Boy Scout Motto is, "Be Prepared" – and I was very serious about Scouting back in the day – I am always amused when I happen by NatGeo's "Doomsday Preppers." But I can say with certainty that they are missing the biggest, most obvious threat: Data Doomsday!
Earlier this week, the digerati assembled at the Gramercy Park Hotel to hear a very proud James Dolan, CEO of Cablevision Systems Corporation and Executive Chairman of The Madison Square Garden Company, gleefully announced the launch of Cablevision's Freewheel WiFi Phone Service.