AI-Powered Data Cleansing: Innovative Approaches for Ensuring Database Integrity and Accuracy

© 2024 by IJCTT Journal
Volume-72 Issue-4
Year of Publication : 2024
Authors : Vijay Panwar
DOI :  10.14445/22312803/IJCTT-V72I4P115

How to Cite?

Vijay Panwar, "AI-Powered Data Cleansing: Innovative Approaches for Ensuring Database Integrity and Accuracy," International Journal of Computer Trends and Technology, vol. 72, no. 4, pp. 116-122, 2024. Crossref,

The proliferation of data across industries has underscored the critical need for high-quality data management practices, particularly data cleansing. Traditional data cleansing methods, while foundational, often fall short in addressing the complexity and scale of contemporary data environments. This research paper delves into the application of Artificial Intelligence (AI) in data cleansing, presenting a paradigm shift towards more efficient, accurate, and scalable data management solutions. By conducting a comparative analysis between traditional data cleansing techniques and AI-powered approaches, this study outlines the significant advantages of leveraging machine learning algorithms and natural language processing for data integrity tasks. The methodology encompasses a review of current literature, an evaluation of various AI models and algorithms in data cleansing, and the presentation of case studies that highlight the practical implications of these technologies in real-world settings. Findings indicate that AI-powered data cleansing not only surpasses traditional methods in efficiency and accuracy but also offers adaptive capabilities essential for managing dynamic data landscapes. This research contributes to the understanding of AI's role in enhancing database integrity and accuracy, offering insights into future directions for integrating advanced AI technologies in data management practices. The implications of this study extend beyond academic interest, providing valuable guidelines for organizations aiming to harness AI for improved data quality and operational excellence.

Data Cleansing, Artificial Intelligence, Database Integrity, Machine Learning Algorithms, Data Quality, Natural Language Processing, Big Data Management, AI-Powered Tools, Data Accuracy, Automated Data Cleansing.


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