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How to Scale the Storage and Analysis of Data Using Distributed Data Grids

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Data parallel programming on a distributed data grid is an important new method for overcoming performance bottlenecks for a broad class of applications. This new method is expected to have important applications in cloud computing over the next few years. Here, Knowledge Center contributor William L. Bain discusses how a distributed data grid can be used to implement powerful, Java-based applications for parallel data analysis.
– A
hallmark of the Information Age is the incredible amount of business
data that companies have to store and analyze. The ability to
efficiently search data for important patterns can provide an essential
competitive edge. For example, an e-commerce Website needs to be able
to monitor online sh…

 How to Scale the Storage and Analysis of Data Using Distributed Data Grids

 How to Scale the Storage and Analysis of Data Using Distributed Data Grids

 How to Scale the Storage and Analysis of Data Using Distributed Data Grids  How to Scale the Storage and Analysis of Data Using Distributed Data Grids  How to Scale the Storage and Analysis of Data Using Distributed Data Grids  How to Scale the Storage and Analysis of Data Using Distributed Data Grids  How to Scale the Storage and Analysis of Data Using Distributed Data Grids  How to Scale the Storage and Analysis of Data Using Distributed Data Grids  How to Scale the Storage and Analysis of Data Using Distributed Data Grids

 How to Scale the Storage and Analysis of Data Using Distributed Data Grids

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