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Leading retail intelligence group Cogenta (www.cogenta.com) has chosen open source technology as the engine for its new retail pricing intelligence platform. The new platform is the first system able to collect and analyse big data retail price information in real-time.

In an ever more price sensitive retail market, up to the minute data can ensure that retailers are able to make even more informed and competitive pricing decisions than previously. By including real-time data in their widely acclaimed UK consumer goods pricing reports, Cogenta ensures that their retailer customer base can exploit the best data available on the market. In addition, as the new platform is far more scalable than other market offerings, retailers can also perform even bigger projects with this data than before.

To deliver these levels of big data performance, Cogenta based the new platform on a fusion of proven open source technologies including: ElasticSearch, MongoDB and RabbitMQ, backed by a SQL data depository. ElasticSearch has won widespread acclaim as a flexible and powerful distributed real-time research and analytics engine for the Cloud. MongoDB is a respected open document database with RabbitMQ operating as a robust messaging system. When combined with Cogenta’s existing big data analytics, the new platform delivers unprecedented levels of real-time analysis and sophistication to the retail environment.

Commenting on the new platform Cogenta’s CTO, Yann Cluchey, noted; “We’ve been able to create a highly scalable platform with levels of real-time data processing and intelligence capabilities far beyond the previous market status quo.  The use of proven Open Source technology allows us the flexibility to deliver better services more quickly than the market has been able to access before.”

Adrian Hobbs, Cogenta’s CEO, echoed Cluchey’s comments adding, “By utilising the latest Open Source technology to ensure unmatched levels of intelligence in real-time, the new Cogenta platform significantly increases the value our clients can derive from the data. And if that means that they are now able to make significant price adjustments even earlier, then the chances are that this would have a very major and positive impact on any retailer’s performance. Naturally then, we are confident that demand will prove to be extremely high for the potential advantages that this leap forward in technology delivers.”