Understanding Data Debt

Data debt refers to the accumulation of data-related problems over time due to the use of various data systems and the storage of data for different purposes. This debt leads to issues in data quality, flexibility, governance, and security. As data volumes grow, the challenge of managing data debt increases, hindering effective analytics, decision-making, and data accessibility. Data debt also poses risks to data security, privacy, and compliance, and adds high costs for maintaining and managing duplicate or obsolete data systems. Despite advancements in technology, adding more systems often exacerbates the data debt problem, necessitating a focus on process and method instead.