Data Quality & Governance: Learn the Essentials Fast

This course offers a clear and practical introduction to modern data governance and data quality management, specifically designed for beginners to intermediate professionals seeking to strengthen their knowledge of how trusted data is built and maintained across enterprise ecosystems.

By the end of this course, you’ll have a strong foundational understanding of how organizations manage trusted data using structured, repeatable workflows. The concepts are presented in a widely applicable manner — making it a great starting point no matter what platform your organization uses, from emerging solutions to well‑established data management environments.

You’ll explore key topics such as:

• Profiling datasets to assess accuracy, completeness, and consistency

• Creating and applying rule-based validation logic to ensure data quality

• Managing business glossaries, metadata, and classification hierarchies

• Tracking and resolving data quality issues through stewardship workflows

• Leveraging AI-driven features for anomaly detection and smart suggestions

• Aligning governance efforts with compliance, risk, and business policies

• Monitoring data assets and understanding how to operationalize governance in real scenarios

Whether you're a data steward, analyst, engineer, or business stakeholder, this course helps you understand how governance and quality work in modern data environments and prepares you for deeper tool-specific learning and project participation.

No prior experience is required — only a curiosity to learn how organizations ensure their data is reliable, usable, compliant, and ready for analytics, AI, automation, and decision-making at scale.