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Distributed Data Mining and Big Data Vision Paper

Intel’s perspective on analytics at the edge

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This paper describes Intel’s perspective on distributed data mining with big data—or the analytics of big data generated by sensors and devices on the edge of networks. The paper includes a discussion of: • The importance of analytics at the edge of networks where some of “biggest,” fastest growing sources for big data are generated • How big data is inherently different from the data managed by traditional data management or business intelligence platforms, and why it matters • A quick overview of emerging technologies including distributed frameworks such as the Apache Hadoop* framework and Apache* MapReduce • Four edge analytics use cases for government (smart cities), retail (the connected store), automotive (intelligent systems on the road), and manufacturing (smart factories)—two utilizing the Hadoop* framework and two focused on intelligent systems data

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