Data must be managed as a valuable business asset. It fuels countless processes — from ESG reporting to complex AI applications. Whatever the use case, the data needs to be reliable and fit for purpose. Only then can organisations build on it, work data-driven, and create sustainable impact.
A solid framework for monitoring and improving Data Quality is essential. Without it, many data issues remain hidden — resulting in risks like poor decisions, compliance failures, and unnecessary inefficiencies.
Data Quality Management
Effective Data Quality Management is the key to realising data’s full potential. It is a continuous process of planning, executing, and controlling activities that apply quality management to data, with the goal to make data fit for its intended use.
This requires a Data Quality framework aligned with the business strategy and, where necessary, compliant with regulations such as BCBS 239 and Solvency II.
Such a framework supports identifying critical data, setting quality rules, detecting and analysing issues early, addressing root causes, and reporting results. This is how organisations gain control over the quality of their data — and therefore over risk, performance, and compliance.
Services we provide
We support the creation of policies, roles, and processes that secure Data Quality — such as a robust framework and Data Quality policy.
We ensure that the right tools and processes are in place to make Data Quality visible and manageable.
Whether you are just starting out with Data Quality or already have a team of seasoned Data Stewards, we provide Data Quality training suited to your organisational maturity.
