How do you balance data quality and data agility in a fast-changing and competitive market?
Data quality and data agility are both essential for any business that wants to leverage data as a strategic asset in a fast-changing and competitive market. Data quality ensures that the data is accurate, consistent, complete, and fit for its intended purpose. Data agility enables the data to be accessed, analyzed, and transformed quickly and easily to meet changing business needs and opportunities. However, achieving both data quality and data agility can be challenging, as they often require different approaches, tools, and trade-offs. In this article, we will explore some of the key factors and best practices that can help you balance data quality and data agility in your data lifecycle.