A global retailer that designs and sells ready-to-assemble furniture, kitchen appliances, and home accessories was searching for innovative ways to offload its use of centralized and cloud data centers for managing hundreds of remote “brick and mortar” storefronts. At the same time, stores continued to generate higher volumes of local, customer-related data, requiring a more distributed data processing model for supporting the stores.

This case study showcases how the retailer bolstered its in-store edge computing environment to lower support costs, simplify management, and maximize uptime.


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