When are Analytics Better in the Cloud?
Public or hybrid deployments can boost analytics for big data with newfound capacity for high-performance capabilities such as preparing data for data mining, scoring data and producing data models. In addition, off-premise environments may be better built to handle unstructured data from Twitter posts or log files and enable more flexible and powerful analytics processing.
The public or private cloud can also provide advantages for prototyping or running proof-of-concept projects for new analytics technologies. Here, the cloud works as the evaluation and benchmarking environment without having to find and customize hardware to install test configurations, MWD reported.
Analytic applications developed especially for or by your team could come together more quickly in a Plaform as a Service offering, MWD states. Taking on a PaaS, the cloud provider is in charge of tasks like on-demand provisioning and the maintenance of software and hardware.
With existing enterprise business intelligence applications already in place, an option like a hybrid cloud environment enables offloading of some data analysis processing or shifting a downstream data mart.
Short-lived ad hoc analysis used on a temporary basis in the cloud can handle sudden, new business conditions, like integration of an acquisition.
SMBs, long a target market for widespread cloud adoption, may find distinct new advantages in deploying certain analytics capabilities. As many SMBs lack the IT infrastructure for an in-house cloud, the public cloud model offers lower upfront cost barriers for analytics or BI and faster access to analysis options. And small or non-existent marketing and sales capabilities may spring up through an as-a-service option.
Here are a half-dozen examples where analytics might be more appropriate as a cloud deployment or as-a-service offering, according to a MWD Advisors report.