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How to improve efficiency on analysing big data on a large number of measurement and verification projects

机译:如何提高大量测量和验证项目中大数据的分析效率

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Big data can be defined as a collection of large and complex data sets which are difficult to process using readily available or traditional data processing applications. These big data sets introduce new challenges such as capture, storage, search, sharing, transfer, analysis, versioning and visualization. This paper present a design philosophy, techniques and experience, from an information technology perspective, in dealing with large quantities of energy data. It provide a vehicle for the general (non-IT) user to increase his or her efficiency in analysing and visualizing energy data for business decisions.
机译:大数据可以定义为大型和复杂数据集的集合,这些数据集很难使用现成的或传统的数据处理应用程序进行处理。这些大数据集带来了新的挑战,例如捕获,存储,搜索,共享,传输,分析,版本控制和可视化。本文从信息技术的角度介绍了处理大量能源数据的设计理念,技术和经验。它为一般(非IT)用户提供了一种提高其分析和可视化能源数据以进行业务决策的效率的手段。

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