Data Security, Quality, and Governance

This unit covers core concepts and practices for ensuring data quality, securing data assets, and establishing data governance in engineering contexts. Students will examine threats and controls (encryption, masking, access control, secrets management), construct governance artifacts (policies, processes, roles), and relate privacy and big data characteristics to practical data management—building on earlier data and programming fundamentals and preparing learners to implement secure, governed data pipelines in the final unit.

Learning Objectives

• Analyze dimensions of data quality and evaluate the impact of poor data quality on engineering workflows using concrete examples and metrics
• Apply core data security techniques (encryption, data masking, network protections, access control, and secrets management) to design a secure data handling workflow for a sample dataset
• Demonstrate the creation of a basic data governance framework by drafting policies, defining processes, and assigning roles that align with data management activities
• Evaluate data privacy concerns and the Five V’s of Big Data to recommend controls that balance data utility, security, and regulatory compliance