DBTA E-EDITION
June 2014 - UPDATE
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Trends and Applications
In "Big Data at Work," Tom Davenport explains to readers why big data is important to them and their organizations, what technology they actually need to manage it, and where to start capitalizing on its potential. Here, the author shares an excerpt from his recent book.
Applying automated analytics to a wide variety of IT and business metrics is rapidly becoming "the next big thing." When considering whether to give the data center the "Moneyball" treatment in 2014, there are two main architectural considerations that need to be evaluated.
A good analytical model should satisfy several requirements, depending on the application area. In order to achieve business relevance, it is of key importance that the business problem to be solved is appropriately defined, qualified, and agreed upon by all parties involved at the outset of the analysis.
Big data analytics hold great promise, but the present methods of mining and managing big data are still evolving and pose serious security and privacy challenges. Confronting these challenges is essential if the potential of big data is to be fully exploited.
The database market is heating up again. Recent venture funding and acquisition announcements from key Hadoop and NoSQL startups are drawing attention to the big data space.