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Big data demands change of mindset, says Thomson Reuters CCO

1/02/2016 by Pascal CALOC


While nearly all organisations are now aware of the benefits big data can offer – some still need to undergo a change of mindset in order to realise big data insights and opportunity, says Debra Walton, Chief Content Officer, Thomson Reuters.

In a blog post for Big Data New Magazine, Walton suggests that firms are being overwhelmed by the sheer volume of information that a big data strategy throws up, urging chief compliance and chief operating officers to focus on "smart" data.

With the amount of data consumers are generating expanding by the day, firms have to find a way of extracting the information that will prove most valuable, she argues.

She also emphasised that the top layer of management shouldn't expect immediate results from big data – even if they are keen to see a quick return on their investment in analytical tools.

"Patience and persistence are key if the return on investment is to be sustainable, or exist in the first place," she wrote.

"The task can be costly, which may dissuade firms from diving in. But an investment now is likely to pay off in the long run -- though a push for immediate results may lead to expectations that can't be fulfilled, undermining the effort."

Another potential hindrance to generating valuable big data insights is "silo syndrome", whereby a lack of common goals leads to poor communication between divisions, making it difficult to get the most out of data.

Walton suggests that firms may be resistant to foster a change in corporate culture out of fear that if too many people know how they're using data, "investment strategies may inadvertently be exposed".

On top of that, there remains a concern that collecting lots of information will make an origination a prime target for hackers and cybercrime. However, with the "gold" that can gleaned from incorporating big data, it's within a firm's interest to find ways to deal with these challenges, Walton concludes. 


Thomson Reuters, Big Data & Analytics

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