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Data warehouse and decision support on integrated crop big data

机译:综合作物大数据上的数据仓库和决策支持

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摘要

The introduction of modern information technologies for collecting and processing agricultural data revolutionise the agriculture practices. The agricultural data mining today is considered a Big Data application in terms of volume, variety, velocity and veracity. Hence, it is a challenge and a key foundation to establishing a crop intelligence platform. The platform, which processes vast amounts of complex and diverse information, will enable efficient resource management and high quality agronomy decision making. In this paper, we designed and implemented a continental level agricultural data warehouse (ADW). ADW is characterised by its (1) flexible schema; (2) data integration from real agricultural multi datasets; (3) data science and business intelligent support; (4) high performance; (5) high storage; (6) security; (7) governance and monitoring; (8) consistency, availability and partition tolerant; (9) cloud compatibility. We also evaluate the performance of ADW and present some complex queries to extract and return necessary knowledge about crop management.
机译:引进现代信息技术,用于收集和加工农业数据彻底改变农业实践。今天的农业数据挖掘在体积,品种,速度和准确性方面被视为大数据应用。因此,建立农作物智能平台是一项挑战和关键基础。该平台,处理大量复杂和多样化的信息,将实现高效的资源管理和高质量的农学决策。在本文中,我们设计并实施了大陆级农业数据仓库(ADW)。 ADW的特点是其(1)柔性架构; (2)来自真实农业多数据集的数据集成; (3)数据科学和商业智能支持; (4)高性能; (5)高储存; (6)安全; (7)治理和监测; (8)一致性,可用性和分区容忍; (9)云兼容性。我们还评估ADW的性能,并提出了一些复杂的查询来提取和返回关于裁剪管理的必要知识。

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