What you'll learn

Trusted data starts with a shared way to describe what is wrong and why it matters. In this course, Introduction to Data Quality and Observability, you will gain the ability to explain how data quality, data reliability, and data observability support better decisions, analytics, and AI outcomes. First, you will explore how quality rules, reliability expectations, and observability signals differ in practical work. Next, you will discover common quality dimensions such as completeness, validity, consistency, uniqueness, accuracy, and timeliness. Finally, you will learn how metadata, lineage, stakeholders, business processes, and critical data elements help teams define a realistic starting scope. When you are finished with this course, you will have the skills and knowledge of data quality and observability fundamentals needed to recognize trust problems and frame an initial initiative clearly.