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Traditional technologies were causing a business impact and slowing things down. We were a partner of Vertica before HP purchased them back in Saso: Justin, maybe you can talk a little bit about that. We had a four-node system setup with multiple terabytes of data. If you think long-term, if you start in the cloud , you want to be able to move out of the cloud.

Another problem is encryption. Are there some metrics of success? Maybe some examples of what one should be looking for and how to measure that. The two factors are the value to the business. The other way to judge it is impact on business. Gardner: One last area on this optimization idea. They will do their cost-benefit analysis.


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  4. Thinking about that, do you expect that companies will be able to do that? One of the reasons I like Vertica is that it has a cloud instance that can run on a public cloud. That same instance, that same architecture runs just as well on bare metal, only faster. Gardner: Chris, last word to you. Instead, they find themselves faced with overwhelming amounts of data and organizational complexity, rapidly changing customer behaviors, and increased competitive pressures. For years SAS customers have evolved their analytics methods from a reactive view into a proactive approach using predictive and prescriptive analytics.

    Reactive vs.

    Big Data Analytics: Disruptive Technologies for Changing the Game

    Source: Bloomberg. One research was conducted and online surveys were sent to corporate members of SCM World and MESA International, with respondents from professional services and software sectors excluded from the analysis. Bill Loconzolo, vice president of data engineering at Intuit, jumped into a data lake with both feet.

    The leading edge of big data and analytics, which includes data lakes for holding vast stores of data in its native format and, of course, cloud computing, is a moving target, both say.