Big Data Commentary Roundup

Source: Customer Experience Matters

Source: Customer Experience Matters

Katie Baker in Grantland: “After spending two days and nights [at the MIT Sloan Sports Analytics Conference] talking and thinking and hearing about data visualization and correlation coefficients and Big Data… and things like ‘Dequantizing the Player Draft Using Extreme Value Theory,’ I probably ought to have prepared myself better before walking down Causeway Street toward TD Garden for a real live Bruins-Canadiens rivalry game. …it mildly upsets me that I can’t really animalistically rah rah even a good scrap with an understandable backstory anymore without having phrases like ‘statistically significant’ pop into my head. Oh well. The more you know, after all, the more you know how much you don’t. But at this point, the majority of people who like sports remain blessed by the eternal sunshine of the statless mind. Midway through the game, TD Garden briefly swelled with a creative chant about star Habs defenseman P.K. Subban: SUBBAN SUCKS! No one had any data to back up this bold and collaborative hypothesis, but they didn’t really need to.”

John Kay writes in “A story can be more useful than maths”: “So while probabilistic thinking is indispensable when dealing with recurrent events or histories that repeat themselves, it often fails when we try to apply it to idiosyncratic events and open-ended problems. We cope with these situations by telling stories, and we base decisions on their persuasiveness. Not because we are stupid, but because experience has told us it is the best way to cope. That is why novels sell better than statistics texts.”

Brett Slatkin in “Own it: Data scientists just do marketing” on One Big Fluke: “If you spend all your time trying to understand your customers you’re doing marketing, not data science. …  The only nuance is these folks do quantitative marketing. When most people think of ‘marketing’ they recall branding, communication, and customer outreach. That may be why most programmers I’ve known seem allergic to ‘marketing’ and disparage the concept. But in the last few years we have more analytical data about our customers than ever before. Storing the data is cheap and easy. We have great tools for data processing and deriving insights about our users. And we have seen the power of small changes leading to big improvements. It has legitimized marketing as an engineering field.”

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About GilPress

I launched the Big Data conversation; writing, research, marketing services; https://whatsthebigdata.com/ & http://infostory.com/
This entry was posted in Analysis, Asking questions, Big Data Analytics, Big data market, Data Science, Data Scientists, Skills, Sports Analytics, Statistics. Bookmark the permalink.

One Response to Big Data Commentary Roundup

  1. Joey Blue says:

    We should all be thinking about story telling and marketing. Even the programmers that don’t like sales and marketing will eventually have to go to the boss and talk about a raise. Or, they may even have to go in for an interview. The better salesman and marketer you are the better chance you have at getting the job you desire. You can even throw a few stories in to help them remember you and to set yourself apart from the other programmers.

    Like

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