If you were to consider conferences as medication, they’d come in two primary forms – those that put you to sleep, and those that keep you awake. In that context, T4G’s Big Data Congress was the equivalent of walking around with a Red-Bull IV.
In his capacity of muse, antagonist, and harlequin for the event, Andreas Weigend – formerly Chief Scientist at Amazon and now social data evangelist – reminded us that while big data is the new oil, like oil we need an eco-system to extract the value, and we were off and running.
Andrew McAffee of MIT then scared the bejeebers out of us with the concept of digital encroachment, showing how rapidly digital labour was supplanting human labour and its impact on society – especially the middle class – and the case for working with machines and big data to “save society”.
Some of the highlights:
- Hilary Mason of bit.ly (who has kind of a mild mannered Clark Kent quality about her) calling for us to think of data as a super-power and to find more “awesome nerds” to obtain, scrub, explore, model and interpret big data.
- Weigend on the Eight Rules of Social Data (Rule #1 – collect everything) and the need to focus on mindset (ensure key makers decision-makers “get” the disruptive nature of big data) before worrying about skill set, tool set or data set.
- Tom Davenport and the notions of continuous rivers of data – the composition, velocity and turbidity will be different each time you dip into it – and understanding the question you want answered, and the data you’ll need to answer it, before diving in.
- Steven Johnson and the concept of networks of related ideas evolving over time (The Slow Hunch), how much innovation is incremental, evolutionary and derives from context rather than great leaps of intuition (The Adjacent Possible), and facilitating the ability of ideas to easily flow from mind to mind (Liquid Networks).
The single biggest take away for me was the potential for big data to re-shape how we tackle the big problems. Picture an entire province doing as one of Weigends’ classes did – spitting into a test-tube and using the DNA to map genetic strengths and weaknesses – then think what that could to for health-care.
My next biggest lesson learned was how much organizations are willing to invest in being able to leverage big data to their advantage. GE investing $2 Billion (yes, you read that correctly) to create a Centre for Analytics (or should that be a Center for Analytics?) was once such example.
And while many practical and bottom line-oriented big data applications were referenced, there was a steady undercurrent of leveraging big data to learn more about ourselves and how we behave.
With all the energy in the room, and the almost palpable sense of light bulbs going off all over the place, I’m very interested in seeing what Saint John, New Brunswick and Atlantic Canada do next with big data.
Learn more by downloading our white paper, ‘Getting A Handle on Big Data Doesn’t Have To Be A Big Headache.’