Cycling the new Golf – and Big Data Problem

By Clive Gold, CTO Marketing, EMC Australia and New Zealand

On Sunday, after almost a decade absence I, (with 9 999 of my closest friends), return to cycling the ‘Gong’. If you aren’t familiar with this charity cycle, it’s from Sydney to Wollongong about 90km (here), which raises money for MS Australia, a great cause and an event EMC has supported for many many years.

A bit of the back story, about a decade ago I had a fairly bad cycling accident, (as we all do). My mistake was my wife was right behind me and once the body healed, she went about dissuaded me from road-cycling. So I’ve been mountain biking for a while, and packing on the weight as you do. This year I decided to pull myself towards myself and this older and abused body could not tolerate jogging anymore I decided to get back on the road!

First a road bike was needed… do you have any concept of how many manufactures and models of frames, seats, group sets, breaks, wheels, etc. there are today? The combinations and permutations are not worth considering, even before factoring your personal attributes and use cases. So, like everyone, I hit the web and begin many long nights on the myriad of “Cycle Forums”.  Where everyone’s opinions’ are black or white, the problem is for any consideration you will find both the black and the white argument, where is the consensus view? Big Data problem one:- how to move from search, to find, to consensus views? If you know of a new nifty utility, please let us know. I have seen some ‘visual search’ sites that try and present all this graphically so the hot spots stick out. But for this large a set of considerations, it would be amazing to see some of the ‘data visualisation gurus’ come up with an answer.

Secondly, get fit and lose weight, so what better way than cycle to work when I’m in Sydney. Good idea until you realise that Sydney roads are without doubt the worst and most cycle-un-friendly in Australia, perhaps on the globe! Now cycling is the fastest growing sport in the country and I’m sure I am not Robertson Crusoe, there has to be others who have done this. Hit the web again, WOW, far beyond what I imagined, people have actual GPS data mashed up with maps to show their preferred cycle route, ordered by source and destination and even ‘use case, (commute to work, Sunday Cycle, etc.) Fantastic until I try and determine the best and safest route to work.. and consolidating a number of maps produces a Christmas tree… every road lights up as someone’s preferred route! Big Data problem two:- how to work with disparate datasets and keep context?

Thirdly .. and so on.. you get the idea, what is they training program, nutritional needs, weather conditions etc.. so much data but not a drop to digest!

Good luck to the people riding for EMC and everyone else, have a fun day.. the weather looks to be warm and no rain!

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2 responses to “Cycling the new Golf – and Big Data Problem

  1. Clive, Good Luck and stay safe….

  2. hey Clive:

    re this “Sydney roads are without doubt the worst and most cycle-un-friendly in Australia, perhaps on the globe!”

    My friend who left Sydney for Sweden, with this as one of his main reasons, tells me that it’s worse in Europe, but for a different reason – it’s the cyclists, not the motorists who make it dangerous and unpleasant.

    It’s a bit like your vendor discussion – they all have pros and cons, but they are different to each other and you have to choose your poison.

    Good luck with the ride.

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