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- W2790486005 abstract "This report details a course on big data analytics designed for undergraduate junior and senior computer science students. The course is heavily focused on projects and writing code for big data processing. It is designed to help students learn parallel and distributed computing frameworks and techniques commonly used in industry. The curriculum includes a progression of projects requiring increasingly sophisticated big data processing ranging from data preprocessing with Linux tools, distributed processing with Hadoop MapReduce and Spark, and database queries with Hive and Google’s BigQuery. We discuss hardware infrastructure and experimentally evaluate the cost/benefit of an on-premise server versus Amazon’s Elastic MapReduce. Finally, we showcase outcomes of our course in terms of student engagement and anonymous student feedback." @default.
- W2790486005 created "2018-03-29" @default.
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- W2790486005 date "2018-08-01" @default.
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- W2790486005 title "A course on big data analytics" @default.
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- W2790486005 doi "https://doi.org/10.1016/j.jpdc.2018.02.019" @default.
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