There are six examples where analytics might be more appropriate as a cloud deployment or as-a-service offering, according to an MWD Advisors report.
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Combing Through Massive Data Sets
Public or hybrid deployments can boost analytics for big data with new-found 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.
Testing Concepts
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.
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Taking on Customized Applications
Analytic applications developed especially for or by your team could come together more quickly in a Plaform as a Service offering. Taking on a PaaS, the cloud provider is in charge of tasks like on-demand provisioning and the maintenance of software and hardware.
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Scaling Out Enterprise BI
With existing enterprise business intelligence applications already in place, an option like a hybrid cloud environment enables the offloading of some data analysis processing or shifting a downstream data mart.
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Responding Quickly
Short-lived ad hoc analysis used on a temporary basis in the cloud can handle sudden, new business conditions such as the integration of an acquisition.
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Branching Out
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.