In today’s data-driven world, ensuring data quality has become the key to success for organizations across industries and academia. Hence, this tutorial begins by exploring the foundational principles of data quality, emphasizing dimensions such as accuracy, completeness, consistency, timeliness, and validity. However, many strategies to improve data quality are costly in terms of processing time, computational resources, and/or the amount of training data required, where quantum computing promises advantages. Hence, this tutorial will briefly introduce quantum computing and focus on its applications to data quality, including a demonstration and open challenges that might open new research directions and business opportunities in improving data quality.