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.

I have a wealth of experience in data quality assurance. I developed the HESA data quality strategy in the mid-1990s and this has fomed the basis of HESA data collections for over twenty years. I have also worked to improve the understanding of quality concepts and  issues across the sector. I spent ten years running an ISO9001 quality management system and have a deep understanding of quality theory as well as practical experience.

Thanks 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