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Blogs > Fern Halper
Analyzing Data in the Cloud
Fern Halper By: Dr Fern Halper, Partner, Hurwitz & Associates
Published: 30th September 2009
Copyright Hurwitz & Associates © 2009
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I had an interesting chat with Roman Stanek, CEO of Good Data last week about the debate over data security and reliability in the cloud. For those of you who are not familiar with Good Data, it provides a collaborative business analytics platform as a SaaS offering.

The upshot of the discussion was something like this:

"The argument over data security and reliability in the cloud is the wrong argument. It's not just about moving your existing data to the cloud. It's about using the cloud to provide a different level of functionality, capability and service than you could obtain using a traditional premises solution—even if you move that solution to the "hosted" cloud."

What does this mean? First, companies should not simply be asking the question, "should I move my data to the cloud?" They should be thinking about new capabilities the cloud provides as part of the decision making process. For example, Good Data touts its collaborative capabilities and its ability to do mash ups and certain kinds of benchmarking (utilizing external information) as differentiators to standard premises-based BI solutions. This leads to the second point that a hosted BI solution is a different animal than a SaaS solution. For example, a user of Good Data could pull in information from other SaaS solutions (such as salesforce.com) as part of the analysis process. This might be difficult with a vanilla hosted solution.

So, when BI users think about moving to the public cloud they need to assess the risk vs. the reward of the move. If they are able to perform certain analysis that they couldn't perform via a premises model and this analysis is valuable, then any perceived or real risk might be worth it.

Reader Comments

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13th October 2009: 'Julian Cook' said:

Good point from good data. As an ISV delivering cloud archive services, our delivery partners and customers are often more impressed by the additional capabilities they get using the cloud than the expected cost savings. If you think about archiving, it’s a given that you can store large volumes of historical data in the cloud cost-effectively, but the real benefit for many is being able to leverage the elastic nature of the cloud and analyse massive volumes of archived data when required. At RainStor, we recently ran a benchmarking exercise on AWS highlighting this point http://tinyurl.com/yg8wjbh.

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