Automating the Future: Enhancing ETL Workflows with RPA and Intelligent Automation
Author(s): Santosh Kumar Vududala
Publication #: 2502064
Date of Publication: 05.03.2021
Country: USA
Pages: 1-11
Published In: Volume 7 Issue 2 March-2021
DOI: https://doi.org/10.5281/zenodo.14883126
Abstract
With the more recent improvements in the BI tool and the exploitation of big data, Extract, Transform, and Load (ETL) processes have become critically important. ETL workflows, in particular, are also associated with problems like slowness, poor performance when managing large amounts of data, and the risk of human intervention. Analysing how RPA and IA can revolutionise ETL, this paper aims to discuss the opportunities for change within the field. In light of this fact, RPA and IA enhance the ways organisations work with data by automating routine efforts, increasing data quality, and enabling instant data processing. The paper also describes the strategies for implementing RPA and IA in ETL and looks at the pros and cons of the whole process. It has been found by applying real-time polymerase chain reaction that experimental results have less processing time and lesser errors. Using comparative analysis, the automated ETL will be contrasted with other traditional methods to show how better it is. The discussion chiefly focuses on future trends and the increasing importance of implementing intelligent automation, especially in the future development of big data.
Keywords: ETL workflows, Robotic Process Automation, Intelligent Automation, Scalability
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