Has big data reached a tipping point in the cloud?


There is no doubt that big data analytics is fast becoming integral to business intelligence. Besides many initial failed projects, primarily due to the massive infrastructure needed to store, process and analyze big data in-house, there is an increasing number of success stories. This gives pause to completely discount the paradigm.

Moving big data analytics to the cloud seems to accompany these successes. It is impossible to ignore the competitive edge gained by organizations leveraging big data analysis. From real-time data analytics facilitating industrial processes to financial trading algorithms, big data is a definitive part of the corporate future.

What needs to be considered is why big data works so much better in the cloud than stand-alone systems. Here are some reasons why cloud-based big data solutions have reached a tipping point in terms of wide-scale industry acceptance.

Big data is a big undertaking

Big data is for all intents and purposes, big. In-house implementations of such projects involve some serious infrastructure, processing power and, above all, time. Many of these projects fail because the skills aren’t available to roll out the complexity and groundwork required to bring these developments to fruition.

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