Data quality refers to the reliability, accuracy, consistency, and completeness of data that is collected, stored, and analyzed for research purposes. Ensuring data quality involves various processes such as data cleaning, data validation, and data verification to make sure that the data being used for analysis is accurate and reliable. Poor data quality can lead to incorrect conclusions and decisions, so maintaining high data quality is crucial for the success of research projects. Researchers often use various tools and techniques to assess and improve data quality, such as data profiling, data auditing, and data governance. Additionally, data quality standards and guidelines are often established to ensure consistency and quality across different research projects.