Data analytics is now a strategic priority for all sizes of organizations across all industries. Yet deploying and managing analytics workloads can be a complex and time-intensive undertaking that requires extensive hardware and software integration and testing.To overcome these barriers and remove complexity and upfront technology costs, many IT organizations are looking to Analytics as a Service (AaaS) solutions. These offerings help data scientists, developers and business users get their analytics applications up and running quickly, while avoiding the costs and time-drain that comes with building a solution from scratch.In these deployments, the analytics applications and the huge datasets that come with them sit at the top of a solution stack that rests on a cloud foundation.To read this article in full, please click her
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