Databricks Certified Data Engineer - Associate
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In the context of data governance within an Azure Databricks environment, a company is looking to implement a strategy that ensures data privacy is considered at every stage of the data lifecycle, from initial design to deployment and beyond. This strategy aims to proactively address potential privacy risks and embed privacy controls into the system's architecture. Considering the need for compliance with global data protection regulations, scalability across different regions, and the minimization of data breach risks, which of the following concepts best describes this approach? (Choose one option)
A
Data privacy by design is a strategy that primarily focuses on securing data through advanced encryption techniques and strict access controls, without necessarily integrating privacy considerations into the system's design phase.
B
Data privacy by design is a methodology that emphasizes improving data quality through rigorous validation and cleansing processes, overlooking the integration of privacy protections into the system's architecture.
C
Data privacy by design is a framework that ensures compliance with data protection laws by enforcing data retention policies and classification, but does not incorporate privacy considerations into the initial design of data systems.
D
Data privacy by design is a holistic approach that involves embedding privacy considerations and protections into the design and development of data systems and processes, ensuring privacy risks are addressed proactively from the outset.