Modern telecommunications are alphabet soups that produce massive amounts of diagnostic data. One particular difficulty in telecom analytics is that the data to be analyzed is produced by mobile entities and reported via ever-changing data transports. The resulting mess can be hard to understand from any single viewpoint, but looking at all of the data together isn’t all that hard if you aren’t afraid of data at scale.
Ted Dunning offers an overview of a real-time, low-fidelity simulation of the edge protocols of such a system to help illustrate how modern big data tools can be used for telecom analytics. Ted demos the system and shows how to analyze the data produced by the simulator using a variety of big data tools including Spark.
Ted Dunning has been involved with a number of startups—the latest is MapR Technologies, where he is chief application architect working on advanced Hadoop-related technologies. Ted is also a PMC member for the Apache Zookeeper and Mahout projects and contributed to the Mahout clustering, classification, and matrix decomposition algorithms. He was the chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems and built fraud-detection systems for ID Analytics. Opinionated about software and data-mining and passionate about open source, he is an active participant of Hadoop and related communities and loves helping projects get going with new technologies.
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