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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.
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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.