Opinion

The challenge of making analytics a scalable capability

Of late, I’ve seen two interesting perspectives on the scalability of analytics. The first was a talk by Colin Shearer of IBM/SPSS at an OR Society Analytics Conference and the second was an essay by Andrew Brust. Both shared a similar common thread – If analytics is to succeed long-term, it needs to find a way […]

Analytics: the twenty-first century virtual laboratory

What’s a laboratory? It doesn’t sound like a trick question, but I was in for a surprise.  I asked Google for a definition and got back the frankly archaic:  “A room or building equipped for scientific research, or teaching, or for the manufacture of drugs or chemicals.”  To me that’s not fit for the second […]

Bias in big data. Which way do you lean?

If you only read one article on Big Data this year, you could do a lot worse than choose The Hidden Biases in Big Data by Kate Crawford.  Big Data evangelists are fond of telling us that having a hunch, then building and testing a model against a data sample is now of historical interest […]

Is big data smart enough to forgive and forget?

Recent events have shown just how appropriate it is that the elephant* is the immediately recognisable symbol for Big Data.  The elephant, of course, never forgets.**  I’m not sure that’s such a good thing in the world of algorithmic behavioural profiling. A story that dominated the UK news pages in recent weeks should make us […]

Why stating predictions with care is a core analytics discipline

I can say, with confidence, everyone reading this is familiar with Predictive Analytics.  It’s called the Weather Forecast.  Not only is it the most familiar example, it’s also one of the most challenging to deliver. And when the predictions don’t quite work out as planned, the most exposed. What has recently befallen the UK Met […]

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