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The Bank of Canada Governor Stephen Poloz speaks the media at a Oakville Chamber of Commerce event in Burlington on June 19, 2013.

The Globe and Mail

The potential of so-called big data – everything from real-time financial transactions to Twitter and Internet traffic – is already being used to fight terrorism and sell products.

This explosion of informal data could also be tapped by the Bank of Canada to help set interest rates and produce more accurate forecasts, according to an article in the bank's latest quarterly review.

"Analysis of the vast quantities of digital information contained in big data can offer fresh insight for the monitoring of economic activity and inflation," according to the article by Nii Ayi Armah of the bank's Canadian economic analysis group.

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"The timeliness of big data could improve real-time decision-making for monetary policy."

The article cites examples, including monitoring of media reports of "shortages" to track inflation expectations or scouring online shopping sites and electronic transaction to monitor retail prices.

But the article cautions that in spite of the enormous potential of big data as a monetary policy tool, it remains "in its infancy" for tracking the economy.

That's because a lot of data exists in highly fragmented "silos" and filtering data into useful chunks is difficult. There are also privacy issues involved in how personal data is collected and used.

The sheer volume can be daunting. It's estimated that 1.8-trillion gigabytes of data was created in 2011 – enough to fill 57.5-billion iPads.

"It remains unclear how best to select, organize and aggregate unstructured data so that they provide meaningful signals about economic conditions, and what analytical tools need to be developed to integrate those signals with information from conventional data sources," according to the article.

The author also suggests that while there's lots of data available it's not clear that particular samples are representative of the entire economy.

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"Harnessing the potential of this profusion of data is challenging," the article concluded.

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