There are many opinions regarding how to handle information storage for big data analytics. By big data analytics, I’m referring to information associated with a data analytics operation that does the analysis in near real-time to present immediately actionable results. The most … Continued
“Enterprises are looking to leverage the power of Hadoop analytics to see if Hadoop-supported applications can drive critical business decisions. Therefore, IT management will need the confidence that their Hadoop-related infrastructure is prepared to stand up to the demands of … Continued
“There isn’t an industry today that’s untouched by Big Data or a company that wouldn’t benefit from the intrinsic value of that data if they could collect, organize, store and analyze it in a cost-effective manner,” said John Webster, Senior … Continued
In my previous article I wrote about the five factors that limit Hadoop’s role in the enterprise datacenter. To recap, the limitations are, Increased storage sprawl Three times as much storage Costly data moves Single point of failure No support … Continued
Of the numerous ways that have emerged in the last few years to do “big data” analytics, none has received more media attention than Hadoop. Hadoop began conceptually with a paper that emanated from Google in 2004 describing a process … Continued
Eight years ago, a friend and I were researching a book we would later call “Inescapable Data – Harnessing the Power of Convergence.” We were after an understanding of what kinds of new information one could produce by blending data … Continued
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