Understanding PCI DSS and Payment Card Security

Speaking at the Retail Business Technology Expo in London, John Lewis's head of IT architecture, Julian Burnett, said that the company is coming to terms with the masses of data being generated across its operations. Here is an excerpt from a write up of his discussion from pcadvisor.co.uk:

"Retailers are awash with [data]," he said. "But how do we make any sense of it? How do we bring to bear some of the value that is locked into the data we have?

He continued: "Big data is a big hype, but an organization like John Lewis — and any other retailer — needs to get its head around how we bring together large amounts of structured and unstructured data in a quick and effective manner, in order to generate some level of insight for how to best serve our customers, and how to best select our products."

New innovations being trialled by the company that are likely to further increase the amount of customer data being generated. Burnett pointed to a trial of a 'magic mirror' augmented reality system involving the creation of a huge database of digital content, while a system to passively 'pinpoint' customers in store to allow better planning of the retail space, is being looked at. John Lewis is also looking into the use of mobile payment platforms and digital wallets, though the company is currently hedging its bets on implementation of any particular system.

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User Comments – Give us your opinion!
  • bill bishop
    5876448
    Excellent article but misleading headline. Big data is getting a lot of hype and there is no question that it is over done. My problem with the headline is that it gives the impression that big data is just big hype and that is not true. Space here does not permit a more complete explanation, but if you want to see what professionals are saying about this take part in the status of big data in retailing survey now open on bickmeetsclick.com. Everyone who completes it gets the results. Bill Bishop
  • Rob Cohen
    5717362
    Newer generation intelligence tools are taking big retail data and creating decision support systems as opposed to just BI tools. Examples are personalization engines that automatically match individual shopper's transaction histories with marketing offers (Sagarmatha is an example), and price intelligence platforms that correlate sales with competitive pricing events such as MarketYze, helping buyers focus only on those market events that actually affect them. REtailers are inundated with data as it is - smart systems help them make sense of it all automatically.
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