Data Validation using ETL – A Theoretical Perspective

S. S, Roshaan J. S, S. V, S. S, Sreemathy J
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引用次数: 0

Abstract

Data is more readily available than ever, but when it is erroneous or insufficient, it can be challenging to interpret. As a result, data validation is essential to improving the quality of data for sound decision-making. The authors have discussed some of the most important concepts and challenges in data validation. It is obvious that human oversight cannot be completely removed from this process. Information priceless human qualities that cannot be taught. Humans are still cautious to take action on decisions that have not been validated by another person, despite today's highly advanced data validation technology or automated approaches. A data validation dashboard can be used by an expert data practitioner to monitor the complete data analysis procedure. The dashboard may make it easier for teams or project managers to assign tasks and resources while also more efficiently monitoring the progress and success of their work. This paper offers insightful discussions of the fundamental ideas, key points, and validation procedure for data validation and quality assurance. Additionally, the article compares several data validation technologies, and several significant industry players are explored. Additionally, the main problems, difficulties, and requirements are explored.
使用ETL进行数据验证——一个理论视角
数据比以往任何时候都更容易获得,但是当它是错误的或不充分的,它可能是具有挑战性的解释。因此,数据验证对于提高数据质量以进行合理决策至关重要。作者讨论了数据验证中一些最重要的概念和挑战。显然,人的监督不能完全从这一进程中消除。信息是无价的人类品质,是无法传授的。尽管今天有非常先进的数据验证技术或自动化方法,但人类仍然会谨慎地对未经他人验证的决定采取行动。数据验证仪表板可由专业数据从业者使用,以监视完整的数据分析过程。仪表板可以使团队或项目经理更容易地分配任务和资源,同时也更有效地监视他们工作的进度和成功。本文对数据验证和质量保证的基本思想、关键点和验证程序进行了深入的讨论。此外,本文还比较了几种数据验证技术,并探讨了几个重要的行业参与者。此外,还探讨了主要问题、难点和要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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