One of the biggest challenges in data-based systems and processes is ensuring that data is of a sufficient quality.
Data quality can be a very tricky concept and data can fail in many different ways. As we try and do more things with data, the assessment of quality and fitness-for-purpose becomes more complex. Addressing data quality issues involves all areas of the data lifecycle and can touch on organisational and cultural issues as well.
Andy has a wealth of experience in data quality assurance. He developed the HESA data quality strategy in the mid-1990s and this has fomed the basis of HESA data collections for over twenty years. Andy has also worked to improve the understanding of quality concepts and issues across the sector. He spent ten years running an ISO9001 quality management system and have a deep understanding of quality theory as well as practical experience.
If you would like to discuss your data quality challenges, please get in touch.
Further reading: Understanding data quality
Further reading: How does data fail?
Further reading: Managing data quality