Research on Data Quality Analysis Based on Data Mining

Abstract

As the process of digitalization continues to advance, big data plays a pivotal role across various industries. However, the quality of data directly impacts the results of data analysis and the accuracy of decision-making. High-quality data can provide a reliable basis for decisions, whereas poor-quality data may lead to erroneous judgments and cause incalculable losses. Therefore, the management and enhancement of data quality have become central issues in contemporary data management. Data mining technology, as a powerful tool, excels not only in extracting valuable information from large-scale datasets but also in demonstrating significant potential in improving data quality. By mining and analyzing the patterns and characteristics hidden within data, it is possible to identify and rectify defects, thereby enhancing the overall quality of data and increasing the reliability of data-driven decision-making. This paper delves into the definition and dimensions of data quality, explores the fundamental principles of data mining technology, and examines its specific applications in data quality analysis, aiming to offer new insights and methods for data quality management.