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 enhance its data governance practices by implementing a solution that provides visibility into data flows, origins, and transformations. The solution should help in understanding data provenance, detecting data quality issues, ensuring compliance with regulatory requirements, and supporting data privacy initiatives. Which of the following processes best addresses these requirements? (Choose one option)
In the context of data governance within an Azure Databricks environment, a company is looking to enhance its data governance practices by implementing a solution that provides visibility into data flows, origins, and transformations. The solution should help in understanding data provenance, detecting data quality issues, ensuring compliance with regulatory requirements, and supporting data privacy initiatives. Which of the following processes best addresses these requirements? (Choose one option)
Explanation:
Data lineage is the process of tracking and managing the movement of data across the data lifecycle. It plays a crucial role in data governance by providing visibility into data flows, origins, and transformations. In an Azure Databricks environment, data lineage can be used to enhance data governance by enabling organizations to understand data provenance, detect data quality issues, ensure compliance with regulatory requirements, and support data privacy initiatives. By leveraging data lineage, organizations can gain insights into data usage, identify potential data risks, and make informed decisions to improve data governance practices.