While the rest of the world may be moving to the cloud, the growth of compute- and I/O-intensive analytics have kept much of their big data workloads for data centers on-premises.
According to an article from TECH TARGET, workloads that are built around mobile devices, cloud services, social technologies, and big data can quickly overpower existing data center infrastructure.
As a result, workloads become unpredictable, have dispersed components, ad can generate, process, and store abundant amounts of data.
As the maturity and cost of the cloud has not yet met organizations needs to experiment with new workload types and despite the flexibility of cloud, the infrastructure that organizations are considering for their big data analytics workloads is predominantly on-premises.