LIMED Laboratory, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria.
Department of Computer Science, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria.
J Med Syst. 2018 Feb 19;42(4):59. doi: 10.1007/s10916-018-0894-9.
The huge increases in medical devices and clinical applications which generate enormous data have raised a big issue in managing, processing, and mining this massive amount of data. Indeed, traditional data warehousing frameworks can not be effective when managing the volume, variety, and velocity of current medical applications. As a result, several data warehouses face many issues over medical data and many challenges need to be addressed. New solutions have emerged and Hadoop is one of the best examples, it can be used to process these streams of medical data. However, without an efficient system design and architecture, these performances will not be significant and valuable for medical managers. In this paper, we provide a short review of the literature about research issues of traditional data warehouses and we present some important Hadoop-based data warehouses. In addition, a Hadoop-based architecture and a conceptual data model for designing medical Big Data warehouse are given. In our case study, we provide implementation detail of big data warehouse based on the proposed architecture and data model in the Apache Hadoop platform to ensure an optimal allocation of health resources.
医疗器械和临床应用的大量增加产生了大量的数据,这在数据的管理、处理和挖掘方面带来了一个大问题。事实上,当管理当前医疗应用的数量、种类和速度时,传统的数据仓库框架不能有效工作。因此,一些数据仓库在医疗数据方面面临着许多问题,需要解决许多挑战。已经出现了一些新的解决方案,Hadoop 就是其中的一个很好的例子,它可以用于处理这些医疗数据流。然而,如果没有一个有效的系统设计和架构,这些性能对医疗管理者来说将没有意义和价值。在本文中,我们对传统数据仓库的研究问题进行了文献综述,并介绍了一些基于 Hadoop 的重要数据仓库。此外,还给出了基于 Hadoop 的架构和用于设计医疗大数据仓库的概念数据模型。在我们的案例研究中,我们提供了基于所提出的架构和数据模型在 Apache Hadoop 平台上实现大数据仓库的详细信息,以确保对卫生资源的优化分配。