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Data migration ecosystem for big data invited paper

机译:大数据邀请论文的数据迁移生态系统

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摘要

Data Migration is the process of moving data from a system or systems to a new environment. Often, it is a sub-activity of a business application deployment. Big data is defined as data that is huge, has heterogeneous data dictionaries and involves complex manipulation. Due to nature of the process complexity and its resources hungry approach in migrating Big Data, special attention is required to have a proven methodology and ecosystem to govern the process. The Data Migration Ecosystem for Big Data is the productive set of interacting processes, practices and environments, to collect data from one location, storage medium, or hardware/software system, to cleanse, transform and transfer it to another. The processes and practices are governed by rules and disciplines, with the goal of ensuring information is complete, of high accuracy and consistent. This paper is based on our experience in migrating data for a Malaysia government agency, which involves approximately 1 billion rows of data from 31 heterogeneous sources / systems. Some of the data migrated was created in the seventies (1970), for which the business logic has since been enhanced or changed. The challenge is further complicated by available data being from proprietary databases that are non-RDMS compliance and includes data that is manually maintained in Microsoft Excel spreadsheets.
机译:数据迁移是将数据从一个或多个系统移动到新环境的过程。通常,它是业务应用程序部署的子活动。大数据被定义为巨大的数据,具有异构的数据字典并且涉及复杂的操作。由于流程复杂性的本质及其在迁移大数据中的资源匮乏方法,需要特别注意以拥有行之有效的方法和生态系统来管理流程。大数据的数据迁移生态系统是相互作用的过程,实践和环境的有效集合,用于从一个位置,存储介质或硬件/软件系统收集数据,以清理,转换并将其传输到另一个位置。流程和实践受规则和纪律的约束,目的是确保信息的完整性,准确性和一致性。本文基于我们为马来西亚政府机构迁移数据的经验,其中涉及来自31个异构源/系统的大约10亿行数据。迁移的某些数据创建于70年代(1970年),此后业务逻辑已得到增强或更改。来自不符合RDMS的专有数据库中的可用数据(包括在Microsoft Excel电子表格中手动维护的数据)使挑战更加复杂。

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