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Big data challenges in information engineering curriculum

机译:信息工程课程中的大数据挑战

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摘要

The amount of accumulated data is growing at unprecedented rates. This data is mainly unstructured or semi structured and comes from different sources in a variety of forms. Recently, a range of supporting storage and distributed parallel computing technologies have been developed and put into use by the sector.The products and implementations include; Apache's Hadoop, data processing framework Map Reduce, distributed big data management system Cassandra and other NoSQL database and data storage systems. Among the major challenges are; data representation, reliable shared storage, efficient algorithms and scalable distributed HW/SW infrastructures. Surprisingly, current curricula lack the necessary components to create awareness and a good understanding of these state of the art concepts and technologies. There is an urgent need for integrating the developments in big data technologies into the educational programs and computing curricula. This need not only is dictated by the industry, but also by the employement dynamics in the related professions. This paper discusses fundemental big data issues and technologies that are considered to be necessary for the existing educational programs in computing, information systems and information engineering areas.
机译:累积数据的数量正在以前所未有的速度增长。该数据主要是非结构化的或半结构化,并以各种形式来自不同的来源。最近,已经开发了一系列支持存储和分布式并行计算技术并由该部门使用。产品和实施包括; Apache的Hadoop,数据处理框架地图减少,分布式大数据管理系统Cassandra和其他NoSQL数据库和数据存储系统。在主要挑战中;数据表示,可靠的共享存储,高效算法和可扩展分布式HW / SW基础架构。令人惊讶的是,目前的课程缺乏必要的组成部分,以创造对这些最新的概念和技术的良好理解。迫切需要将大数据技术的发展集成到教育计划和计算课程中。这不仅需要由行业决定,而且还需要相关专业的就业动态。本文讨论了计算,信息系统和信息工程领域现有教育计划所必需的基础大数据问题和技术。

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