Real-Time Big Data Analytics: Real-Time Big Data Analytics by Mike Barlow

By Mike Barlow

5 - 6 years in the past, analysts operating with immense datasets made queries and received the implications again in a single day. the knowledge global was once revolutionized many years in the past whilst Hadoop and different instruments made it attainable to get the implications from queries in mins. however the revolution maintains. Analysts now call for sub-second, close to real-time question effects. thankfully, we've got the instruments to convey them. This document examines instruments and applied sciences which are using real-time enormous information analytics.

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By Mike Barlow

5 - 6 years in the past, analysts operating with immense datasets made queries and received the implications again in a single day. the knowledge global was once revolutionized many years in the past whilst Hadoop and different instruments made it attainable to get the implications from queries in mins. however the revolution maintains. Analysts now call for sub-second, close to real-time question effects. thankfully, we've got the instruments to convey them. This document examines instruments and applied sciences which are using real-time enormous information analytics.

Show description

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Additional resources for Real-Time Big Data Analytics: Real-Time Big Data Analytics

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Mike is coauthor of The Executive’s Guide to Enterprise Social Media Strategy (Wiley, 2011) and Partnering with the CIO: The Future of IT Sales Seen Through the Eyes of Key Decision Makers (Wiley, 2007). He is also the writer of many articles, reports, and white papers on marketing strategy, marketing automation, customer intelligence, business performance management, collaborative social networking, cloud computing, and big data analytics. Over the course of a long career, Mike was a reporter and editor at several respected suburban daily newspapers, including The Journal News and the Stamford Advocate.

But that isn’t the way the human mind works. Human memory is more like flash memory. We have lots of specific knowledge that’s already mapped — that’s why we can react and respond much more quickly than most of our machines. Our intelligence is distributed, not highly centralized, so more of it resides at the edge. That means we can find it and retrieve it quicker. ” As information technology systems become less monolithic and more distributed, real-time big data analytics will become less exotic and more commonplace.

Info organization to make the right decisions,” says Rajaram. “The creation of analytics and the consumption of analytics are two different things. You need processes for translating the analytics into good decisions. Right now, everyone thinks that analytics technology is sexy. But the real challenge isn’t transforming the technology — the real challenge is transforming the people and the processes. info About the Author Mike Barlow is an award-winning journalist, author and communi‐ cations strategy consultant.

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