Big Data Bungee Jumping

The Kawarau Bridge Bungy, pictured here, is the earlist commercial bungy operation. Queenstown, New Zealand Applying data science to business, and bungee jumping, have too much in common. There is the committment from the top — in bungee, that’s your brain — that you’re going to make the jump. WIthout this committment, you are going nowhere,Continue reading “Big Data Bungee Jumping”

Predicting the Past

Predictions are guesses about the past, present, or future. Prediction is not reporting: reporting is an organized recap of what is known. Why predict the past? Predicting the past is the starting point for predicting the future. Wait, don’t we know what the past is/was? Not usually. For example, economic events are so hard to identify and measureContinue reading “Predicting the Past”

Marketing in the Digital World

As customers, we experience digital transformation all the time—perhaps almost every day. In the past decade alone, the ways we consume music, movies, photography, news, retail, and travel have changed utterly. We are on the cusp of similar transformation of transportation and manufacturing, with the advent of onboard computers in cars, driverless cars, and 3DContinue reading “Marketing in the Digital World”

Yes, Your Data is Crap

Filled with despair because your data is a mess? Welcome to the club, and it is a big one: everyone’s data is a mess. It is always incomplete, inaccuarate, out-dated, redundant, plagued with typos, and unavailable in the desired timeframe. It can’t truly answer the questions you need to ask right now, and the questionsContinue reading “Yes, Your Data is Crap”

Big Data: Buyers Beware

If you are working through your Big Data roadmap and hoping for guidance from the Google, well, hope may be all have. I recently studied the top offerings for my search “big data buyers guide.” These docs clearly state that its complicated, and there are a lot of choices. Good to know. One piece IContinue reading “Big Data: Buyers Beware”

Better Know a Data Scientist

Michel Manago is CEO of Kiolis, a Paris-based startup that develops software for personalization and recommendation. I interviewed Michel about the MyCoachNutrition project, which applies case-based reasoning and collaborative filtering technologies to guide subscribers to eat and exercise well. It strikes me that the project combines 3 of Michel’s keenest interests: algorithms, starting companies, andContinue reading “Better Know a Data Scientist”

How You Know Your Registration Forms Need Work

It took perhaps 9 tries, and 12 minutes, to register at UPS.com. OK, I admit I am not patient with reading instructions, especially about what constitutes an acceptable ID (because no one wants to use their email address!). But I got the rules down by the third try, which does not explain tries 4-8. Nothing, inContinue reading “How You Know Your Registration Forms Need Work”

Untargeted (and Undirected) Advertising

Isn’t this a lovely map? I call it an Ad-Map, and I sometimes use them to get about a strange town. Businesses pay to be listed, tourists get an orientation. Tragically, at least for advertisers and tourists, maps such as this are of little use. Advertisers in each category are listed in seemingly random order. Numbers onContinue reading “Untargeted (and Undirected) Advertising”

Google Offer for Nobody

My weather app offered me this banner this morning: OK, Google, take me to the nearest hair salon. (Try it now) I’ve been looking for a new salon. “Nearest” has never been in my criteria. Under 10 miles would be a plus, but “nearest”, nope. Granted, there are certainly people who LOOK as though that was howContinue reading “Google Offer for Nobody”

Data Science and Not-So-Big Data

Statisticians joke (yes, they do!) that half the job is wrestling the data into shape, half is performing useful analyses, and half is explaining the findings. The data wrestling too often expands to consume all my time, leaving me too ennervated to find any findings. Big Data is what got everyone so excited about data science. But BiggerContinue reading “Data Science and Not-So-Big Data”