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From Big Data to Smart Data: Application to performance management

机译：从大数据到智能数据：应用于性能管理

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摘要

In the context of digitalization, some companies are considering a transition to Industry 4.0 to ensure greater flexibility, productivity and responsiveness. The implementation of a relevant performance management system is then a real necessity to measure the degree of achievement of these objectives. In the era of Industry 4.0, the potential access to large amounts of data, i.e. Big Data, poses new challenges to the design and implementation of these systems. With the exponential growth of data generated from different sources, there is a need for extensive exploitation of data for performance management. Given the large volume of data, the speed at which it is generated and the variety of data sources, the manufacturing sector is facing with the challenge of creating value from large data sets. This paper introduces some potential benefits of Big Data for business and in particular its role in performance management systems. However, the key idea is that Big Data are not always neither available nor necessary. Authors focus on the concept of smart data, the result of the transformation of Big Data, and define a set of necessary and sufficient conditions the data should satisfy to be considered as Smart. The paper presents some methods of smart data extraction. Such smart data will be used to feed the performance management system in order to obtain more accurate, timely and representative key performance indicators.
机译：在数字化的背景下，一些企业正在考虑到工业4.0的过渡，以确保更大的灵活性，效率和响应。相关的绩效管理系统的实施是那么现实的需要来衡量这些目标的实现程度。在工业4.0，大量数据的潜在访问的时代，即大数据环境中，对这些系统的设计和实施新的挑战。来自不同来源的数据的指数级增长，有必要进行广泛的开发数据的绩效管理。鉴于大量的数据，在它被产生的速度和各种数据源，所述的制造部门面临与创建从大的数据集值的挑战。本文介绍了大数据的一些潜在的好处业务，特别是其在绩效管理系统的作用。然而，关键的想法是，大数据并不总是既不可用，也无必要。作者专注于智能数据，大数据的变换的结果的概念，以及定义一组的数据应满足被认为是智能的充分必要条件。本文介绍了智能数据抽取的一些方法。这种智能的数据将被使用，以获得更准确的，及时的和有代表性的关键绩效指标来养活绩效管理体系。

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