Data Security, Governance, and Quality

This unit introduces students to data quality concepts and the core principles and practices of data security, privacy, and governance. Learners will assess threats, apply technical controls (encryption, masking, access control, secrets management), and develop governance artifacts (policies, processes, roles) to prepare for building secure, governed data pipelines.

Learning Objectives

• Analyze data quality issues using the data quality hierarchy and prioritize remediation actions for sample datasets.
• Apply core data security techniques—including encryption, data masking, access control, network protections, and secrets management—to design protection strategies for data at rest and in transit.
• Evaluate common threats to data security and privacy and recommend appropriate mitigation and compliance approaches.
• Demonstrate the components of a data governance framework by creating policies, processes, and role definitions and explaining how governance integrates with data management and the Five V’s of big data.