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Big-data solutions are becoming more and more prevalent in the industry today, as cheap commodity hardware and open source solutions like Hadoop and MapReduce are making super-computing efforts affordable for even the smallest of organizations. Hardware and software that is capable of crunching large numbers and filtering through peta-bytes of data are no longer the exclusive domain of big governments and Big Blue, and this means that more and more software engineers are addressing enterprise challenges with big-data solutions.
Big data problems are no longer the exclusive domain of mega-portals and the Bay Area behemoths.
The future of big-data
Many spectators in the industry tend to think that big data plays are only for the mega-sites like Amazon and Google, but nothing could be further from the truth. In fact, many Java EE developers who have played around with presentation tier technologies like JavaServer Faces, Portal Servers and CMS integration may be surprised for find out that it is often these client-tier technologies that are pushing big-data solutions to new limits. Without even knowing it, many organizations are fighting a big data problem as they try to figure out how to match individual users with the right needle of information, given the haystack of data feeds available today.
To see how organizations are looking towards the future and leveraging big data technologies like Hadoop, MapReduce, Cassandra and MongoDB, Jason Tee, a Senior Software Engineer and regular contributor to TheServerSide explores some of the big data trends that are emerging as we get through the first quarter of 2013 in the following feature article:
A look at big-data today
Of course, talking about trends often means prognostication. So why not go beyond they crystal ball and find out how organizations are actually leveraging big data solutions today? In this video interview with Harish Ramachandran, co-founder and project manager at CIGNEX Datamatix, we discover how consultants on the ground are tackling the big data problems that managing and making sense of voluminous amounts of content presents: How 'big data' solutions solve real-time content management problems
And finally, in this feature entitled Why content management problems need big-data solutions, Cameron McKenzie, the Editor-in-Chief of TheServerSide.com, explores why big data solutions are such a perfect fit for the content management space. Discover how smart organizations are cost effectively using a combination of cloud based technologies and open source tools to affordably and effectively solve big data problems.
Architecting for a big-data future
Big data problems are not the sole domain of the mega-portals and the San Francisco Bay Area behemoths like Amazon and Google. As even small to medium size organizations aggregate more and more data, making sense of that data in a way that both scales and meets modern performance demands requires a big-data approach, and using the aforementioned articles to learn how these technologies are being effectively used today will help software engineers and enterprise architects more effectively design big data solutions for the future.
Big-data article recap:
Big data trends: Big things in store for 2013 by Jason Tee
How 'big data' solutions solve real-time content management problems with Harish Ramachandran
Why content management problems need big-data solutions by Cameron McKenzie