Automated Data Governance in Practice

This introductory course on DataGovOps is designed to provide a solid understanding of the value of integrating data governance practices with DataOps methodologies. Join instructor Jonathan Reichental as he explores the principles of DataGovOps, focusing on how to ensure data quality, security, and compliance within agile and collaborative development environments. Plus, learn about the types of tools that enable the automation of data governance. By the end of the course, you will be equipped to propose and create a DataGovOps strategy for your organization.

Learning objectives
Define and differentiate between data governance, DataOps, and DataGovOps, demonstrating their understanding through a written explanation of each concept and their interrelationships.
Identify and describe at least five specific functions of DataGovOps, including automation of data governance processes, regulatory compliance, data lineage management, and monitoring and reporting, as evidenced by their ability to provide concrete examples for each function.
Demonstrate an understanding of DataGovOps solution categories by comparing and contrasting at least three different tools or approaches (such as automation, collaboration, and integration tools), and explaining how each contributes to effective DataGovOps implementation.
Develop a basic DataGovOps implementation strategy, including elements of training, scaling, and communication, as demonstrated through the creation of a sample implementation plan for a hypothetical organization.
Identify and analyze potential challenges in deploying and managing DataGovOps, and propose mitigation strategies for at least three common implementation obstacles, as evidenced by a case study analysis or problem-solving exercise.