Databricks Certified Data Engineer - Professional
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The data engineering team aims to create a multiplex bronze Delta table sourced from Kafka, featuring the schema: key BINARY, value BINARY, topic STRING, partition LONG, offset LONG, timestamp LONG. Given that the value column contains Personal Identifiable Information (PII) for certain topics, the team plans to implement Access Control Lists (ACLs) at partition boundaries to limit access to this sensitive data. Considering the schema and the requirement, which column is optimal for partitioning to enhance security?
The data engineering team aims to create a multiplex bronze Delta table sourced from Kafka, featuring the schema: key BINARY, value BINARY, topic STRING, partition LONG, offset LONG, timestamp LONG. Given that the value column contains Personal Identifiable Information (PII) for certain topics, the team plans to implement Access Control Lists (ACLs) at partition boundaries to limit access to this sensitive data. Considering the schema and the requirement, which column is optimal for partitioning to enhance security?
Explanation:
Partitioning tables can significantly bolster security measures. By segregating sensitive data (like PII) from non-sensitive data into distinct partitions, it becomes feasible to apply tailored security controls to the sensitive partitions. *Personal Identifiable Information (PII) encompasses any data that can directly or indirectly identify an individual, such as a user's name or email address. In this scenario, partitioning by topic allows for the effective application of ACLs to safeguard PII data.