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A review and future direction of agile, business intelligence, analytics and data science

机译:敏捷,商业智能,分析和数据科学的回顾和未来方向

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Agile methodologies were introduced in 2001. Since this time, practitioners have applied Agile methodologies to many delivery disciplines. This article explores the application of Agile Methodologies and principles to business intelligence delivery and how Agile has changed with the evolution of business intelligence. Business intelligence has evolved because the amount of data generated through the internet and smart devices has grown exponentially altering how organizations and individuals use information. The practice of business intelligence delivery with an Agile methodology has matured; however, business intelligence has evolved altering the use of Agile principles and practices. The Big Data phenomenon, the volume, variety, and velocity of data, has impacted business intelligence and the use of information. New trends such as fast analytics and data science have emerged as part of business intelligence. This paper addresses how Agile principles and practices have evolved with business intelligence, as well as its challenges and future directions. (C) 2016 Elsevier Ltd. All rights reserved.
机译:敏捷方法于2001年引入。从那时起,从业人员就将敏捷方法应用于许多交付学科。本文探讨了敏捷方法论和原理在商业智能交付中的应用,以及敏捷如何随着商业智能的发展而发生了变化。商业智能的发展是因为通过互联网和智能设备生成的数据量呈指数增长,从而改变了组织和个人使用信息的方式。采用敏捷方法论的商业智能交付实践已经成熟。然而,商业智能已经发展为改变了敏捷原则和实践的使用。大数据现象,数据的数量,种类和速度影响了商业智能和信息的使用。快速分析和数据科学等新趋势已作为商业智能的一部分出现。本文探讨了敏捷原则和实践如何随着商业智能的发展而发展,以及其挑战和未来方向。 (C)2016 Elsevier Ltd.保留所有权利。

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