This course offers a comprehensive exploration of data governance principles and practices within the realm of data science and analytics. Participants will delve into the regulatory landscape surrounding data governance, understanding the principles, guidelines, and methodologies essential for establishing effective governance frameworks. Topics include data quality management, metadata management, data catalogs, classification, security, access control, privacy management, master data management (MDM), and the integration of data governance into advanced analytics processes. The course emphasizes collaboration, communication, and continuous improvement as critical aspects of successful data governance initiatives in data science and analytics environments.

Who This Course Is For:

This course is intended for professionals working in the field of data science, analytics, and data governance. It is suitable for data scientists, data analysts, data engineers, data governance specialists, compliance officers, data stewards, and anyone involved in managing or analyzing data for insights and decision-making. Additionally, individuals in roles related to IT, data management, regulatory compliance, and enterprise architecture will find value in understanding how data governance principles apply specifically to data science and analytics contexts.