The quality of data used to train ML models significantly affects the quality of analytics and ML-based products and services. Therefore, data quality management is essential to the success of analytics and ML technology.
ISO/IEC 5259-3 specifies the requirements and guidance for establishing, implementing, maintaining and continually improving data quality for analytics and ML. This global standard specifies quality management process requirements and guidance, as well as the reference process and methods that can be tailored to meet ISO/IEC 5259-3 requirements.
It enables organizations to implement and operate data quality measures, management and related processes with sufficient controls throughout the data life cycle.
The requirements and recommendations are generic, to apply to all organizations, whatever their type, size or nature. ISO/IEC 5259-3 does not define detailed processes, methods or measurements.