The importance of data quality in business decisions and best practices for managing it effectively. It defines data quality as accurate, reliable, and relevant information for intended use cases. The importance of governance and ownership in data management is also explained through a waterworks system analogy. 

The need for cleansing, standardization, and enrichment to improve data quality. It also covers best practices for managing data quality, such as identifying relevant metrics, designing monitoring strategies, and tailoring metrics to stakeholders' needs. The role of emerging technologies, such as machine learning, in improving data quality and ethical considerations around data quality are also discussed. Focusing on data accuracy, consistency, completeness, and integrity is crucial for informed decision-making and business growth.