by Angela Guess
Adrian Bridgwater recently wrote in Forbes, “The unfortunate truth is, big data has a lot of enemies… Enemy #1 – IT architecture. Sumit Nijhawan, CEO & President of Infogix argues that technology itself is the first major big data enemy. More specifically, Nijhawan is referring to the architectural challenge of integrating ‘elements’ and data models for big data, which require the proper planning of design and architecture. ‘Data veracity and data silos are the biggest technical challenges, architecturally. Diverse data sources and repositories make it difficult to keep data consistent and accurate all the time. To fix the issue we must implement means to identify data redundancies and inconsistencies by appropriately planning data management and governance strategies,’ he said.”
Bridgwater continues, “Enemy #2 – Amateur data science. Pentaho director of enterprise solutions Wael Elrifai argues that big data has given rise to many people who now want to call themselves data scientists — and that this trend has led to a group of people who derive all manner of bizarre, unreliable and incorrect conclusions. ‘That’s what happens when you apply statistical techniques without understanding how they work,’ said Elrifai. ‘If I’m interviewing someone who can’t explain BLUE, selection bias, or tell me the difference between Bayesian and Frequentist inference, then the interview is over (surprisingly few can). The power of big data must come with responsibility. You wouldn’t put a 14 year-old in the driver’s seat of a Scuderia Ferrari… they’d have incredible power at their disposal but the odds of a good outcome would be statistically slim!’”
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