Data Governance for the AI and Intelligence Era

In an era driven by artificial intelligence and machine learning, data is an organization's most valuable asset, but only if it is managed, secured, and governed correctly. Establishing a solid data governance framework is essential to mitigate risks, ensure compliance, and unlock the true potential of modern intelligence systems. This text-only course provides a clear pathway to understanding how data governance operates today. You will transition from knowing basic data concepts to confidently designing and implementing governance strategies that support ethical AI deployment, robust data quality, and regulatory compliance. What you'll learn: - Understand the core principles of data governance, data stewardship, and metadata management. - Design framework policies that address data privacy, security, and compliance with modern regulations. - Manage data quality and lifecycle requirements for artificial intelligence and machine learning models. - Explore modern data architectures including data catalogs, data mesh concepts, and vector database governance. - Apply ethical guidelines to data collection, storage, and algorithmic decision-making. - Establish roles and responsibilities within a data governance council or working group. You will start with foundational definitions and key terminology before exploring practical strategies for policy creation, risk management, and alignment with modern AI systems. The content is structured logically to build your confidence step-by-step through clear written explanations and real-world scenarios. This course is designed for beginners, aspiring data stewards, business analysts, and managers who want to understand data governance without needing prior technical or coding experience. Start your journey toward mastering data governance in the intelligence age today.