GlobalData gives thumbs up to Walmart/Microsoft deal

Walmart’s five-year strategic partnership with Microsoft is more about AI dominance than cloud reach, according to GlobalData.

At first glance, the retailer’s announcement that it would use the Microsoft cloud platform and desktop apps across its entire business looks to be a direct shot across the bow of Amazon the retailer and Amazon the provider of public cloud services with Amazon Web Services (AWS), notes Brad Shimmin, technology analyst at GlobalData.

‘‘Certainly from Walmart’s perspective as a cloud retailer, this partnership means the world in terms of matching Amazon blow-for-blow in reach and scale,” he says. “And from Microsoft’s vantage point, it stands as unassailable proof that it's indeed ready to lead the hyperscale public cloud provider marketplace. That’s true at least in terms of proving Microsoft’s ability to attract mega brands like Walmart.com and Samsclub.com. But there’s a lot more to this deal than simple one-upmanship in the race to cloud dominance.”

For Walmart to successfully compete against Amazon as a retailer, it will need to beat the e-commerce giant at its own game. That means speeding up its effort to deploy a cashier-less checkout system across a sizable brick and mortar footprint. For that, the company does not need backend scalability per say. Rather, it needs a partner capable of solving Big Data problems, wrangling Internet of Things (IoT) devices and plying artificial intelligence (AI), all from the vantage point of a single cloud platform. This is the underlying technological current flowing beneath the Microsoft and Walmart partnership. 

‘‘By partnering with Microsoft, Walmart’s internal development staff can work within the confines of a lifecycle-complete environment that blends Microsoft’s own best of breed software (SQL Server, Office 365, etc.) with open source solutions such as Apache Hadoop and Tensorflow, all supported by a set of rapidly consumable services designed to solve domain specific tasks like predictive modelling, visual recognition, device management and data analysis,” Shimmin concludes.

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