Using In-Memory Computing to Simplify Big Data Analytics

October 2, 2012

The “big data” revolution is upon us, fed by the need in both the public and private sectors to quickly analyze large datasets for important patterns and trends. With big data analysis, ecommerce vendors can target customers more precisely, financial analysts can quickly spot changing market conditions, manufacturers can tune logistics planning, and the list goes on. They all need powerful, easy to use analysis tools to maintain a competitive edge. Read more…

By Nicole Hemsoth

Using In-Memory Data Grids for Global Data Integration

July 2, 2012

By enabling extremely fast and scalable data access even under large and growing workloads, in-memory data grids (IMDGs) have proven their value in storing fast-changing application data, such as financial trading data, shopping data, and much more. As organizations work to efficiently access their critical business data across multiple sites or scale their processing into the cloud, the need rapidly has grown to quickly and seamlessly migrate data where it is needed. The use of IMDGs creates an exciting opportunity for organizations to employ powerful global strategies for data sharing. Federating IMDGs across multiple sites enables seamless, transparent access to data from any site and provides an ideal solution to the challenge of global data integration. Read more…

By Nicole Hemsoth

How to Scale the Storage and Analysis of Business Data Using a Distributed In-Memory Data Grid

June 4, 2012

A hallmark of the Information Age is the incredible amount of business data that companies have to store and analyze, so-called “big data.” The ability to efficiently search data for important patterns can provide an essential business edge. Using an in-memory data grid with built-in analytics can provide near real-time analysis to keep you ahead of the competition. Read more…

By Nicole Hemsoth

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