IoT Goes Real-Time, Gets Predictive – Glassbeam Launches Spark-based Machine Learning

(Excerpt from original post on the Taneja Group News Blog)

In-Memory processing was all the rage at Strata 2014 NY last month, and the hottest word was Spark! Spark is big data scale-out cluster solution that provides a way to speedily analyze large data sets in-memory using a “resilient distributed data” design for fault-tolerance.  It can deploy into its own optimized cluster, or ride on top of Hadoop 2.0 using YARN, (although it is a different processing platform/paradigm from MapReduce – see this post on GridGain for a Hadoop MR In-memory solution).

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Mining the Data Your Clients Produce: Glassbeam SCALAR Lights Up Value

(Excerpt from original post on the Taneja Group News Blog)

This week Glassbeam announced a new solution for vendors whose products in the hands of clients produce mountains of potentially valuable “back-end” data. Mining that data which can include streams of ongoing customer site configurations, usage, status, location or really any relevant sensor results can help drive vastly better customer support and satisfaction, new and timely revenue opportunities, and better informed product management decisions.  It might seem straightforward to extract value out of big data once you have it, but trying to “home grow” processing and coherent analysis of PB’s of “multi-structured” files to feed all those business processes by using IT logfile utilities or low-level Hadoop coding could take a big effort and fall far short of spectacular. 

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