Maintaining data quality during storage involves several practices. Regular data cleaning is essential to identify and correct errors. Data validation rules can be set up within databases to ensure that only appropriate data is entered. Version control systems track changes made to datasets, helping to avoid inconsistencies. Additionally, backup protocols ensure that data is not lost due to technical failures.
