Posted in machine learning, tagged Big Data, DECC on June 15, 2015|
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There’s a lot of noise about Big Data, with much of it in the energy space. The rise of the Internet of Things, self-learning thermostats, the success of O-Power – all are linked to the generation and automated processing of massive datasets.
The hype machine promises that Big Data will solve all sorts of problems and make the world a better place.
But hype or no hype, personally I hate Big Data.
I can hear the sharp intake of breath at Guru’s PR company, who’ve done a great job getting press coverage for “Big Data” work that we’ve done for the Department for Energy and Climate Change. Bear with me guys, I’ll explain in this post.
First, a clarification of terms: there’s a tendency to refer to any large dataset as Big Data, even when it isn’t. If you’re not sure what Big Data is, here’s a nice background piece by Tim Harford, the FT’s undercover economist.
So what’s wrong with Big Data? Here are some examples:
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