Data Governance vs. Data Quality Data governance and data quality are closely related, but different concepts. The major difference lies in their respective objectives within an organization’s data management framework. Data quality is primarily concerned with the data’s condition. It…

Data forms the foundation of the modern insurance industry, where every operation relies on digitized systems, including risk assessment, policy underwriting, customer service, and regulatory compliance. Given this reliance, insurance companies must process and manage data effectively to gain valuable…

Every digital interaction generates data. This data can provide invaluable insights and drive effective decision-making when managed effectively. However, according to a survey, up to 68% of data within an enterprise remains unused, representing an untapped resource for driving business growth….

What is a data quality framework? A data quality framework is a set of guidelines that enable you to measure, improve, and maintain the quality of data in your organization. The goal is to ensure that organizational data meets specific…

Generative AI has had a transformative impact across numerous sectors and industries — and data management is no exception. The full extent of GenAI’s implications for data governance is yet to be determined. Areas such as data access, extraction, and…