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unCon 2013 Session: Overcoming the Challenges of Making Big Data Useful

Moderator: Ola Mayer, Attunity
Today we led a great discussion at MassTLC
unConference on the challenges that organizations have around moving Big Data
to stay competitive and gain business insights. As always, in typical
unConference style, the discussion evolved into many interesting directions
including talking about what Hadoop is, data co-location, storing aging data
and how to architect your datacenter information repositories in the face of
large amounts of data and the need for timely analytical insights. During the
session, we had approximately 20 participants with different backgrounds and
field expertise including medical and hospital IT solutions, robotics, IT and
consulting companies.
What we heard from the participants was that
several are still struggling with how to store and analyze data and still have
yet to focus on how to actually get the data there. That said, several data
integration challenges emerged in discussions.
As the session evolved, an interesting use
case surfaced describing a hosted environment that deals with, on the front
end, collecting millions of OLTP transactions from millions of customers,
including large supermarket chains, and on the back end deals with the need to
provide real-time business insights from the data, analysis of the newest
collected data, and historic data going back two years and further. This
challenge includes both the need to collect the data quickly, but also the
ability to deliver to a central repository that will help with data analysis.
It is cases like this where a fast, robust data integration solution can
provided added-value by enabling the data delivery in near real-time without
consuming too many resources on the front end.
Overall, the session flushed out the problems
that organizations are facing today when dealing with large and continuous
amounts of Big Data. It was clear that these organizations have a long way to
go and face many challenges along their journey to address their needs. It was
satisfying to help them identify best practices and approaches for managing
efficient data delivery and analytics.
Ola Mayer


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