AI-Powered Data Engineering: Revolutionizing Data Processing and Analytical Workflows

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December 28, 2020

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Data is expanding at a very faster rate, hence, there is need to apply smart methods on the handling and analyzing of the information. This paper will explore, in detail, how AI plays a part in data engineering; with specific reference to the impact of AI on data engineering work flows. The paper also discusses key opportunities in conventional data science which includes scalability, real time data processing, and data quality assurance. It recruits goals that should be realized through the leverage of artificial intelligence in data integration, the data pipeline, and modelling. Proposing the probabilistic model, focusing on the questions of the machine learning algorithm, and natural language processing, the work introduces the notion of intelligent data engineering. Special attention is paid to the experimental evaluations, which confirm the efficiency of the offered solution in regard to the increased velocities, decreased inaccuracy, and optimal rates of analysis as to the traditional techniques. The findings underscore that AI can make the data engineering for better by giving additional freedom in its process. Thus, in this work, it is suggested that AI should be further developed for application in data engineering in order to meet increasing demands of data-driven business for change and differentiation.

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