ETL with Spark SQL Flashcards
6 cards from real Databricks Certified Data Engineer Associate practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 ETL with Spark SQL flashcards as text
How does ETL with Spark SQL deliver business value?
Answer: By reducing risk, improving efficiency, and enabling informed decisions
ETL with Spark SQL delivers business value through risk reduction, efficiency gains, and informed decision-making.
What is the governance framework for ETL with Spark SQL?
Answer: Defined roles, responsibilities, policies, and accountability structures
Governance for ETL with Spark SQL includes defined roles, responsibilities, policies, and accountability.
How should ETL with Spark SQL be communicated to stakeholders?
Answer: Regular updates with clear, actionable information and metrics
Stakeholder communication about ETL with Spark SQL should be regular with clear, actionable information.
What emerging trends are affecting ETL with Spark SQL?
Answer: Technology advances, increased automation, and evolving industry practices
Technology advances and evolving practices continuously shape how ETL with Spark SQL is approached.
How is ETL with Spark SQL tested or validated in practice?
Answer: Through regular testing, audits, and structured validation exercises
ETL with Spark SQL should be regularly tested and validated through appropriate exercises and audits.
What scalability considerations apply to ETL with Spark SQL?
Answer: Maintaining quality and consistency as scope and complexity grow
Scaling ETL with Spark SQL requires maintaining quality and consistency across growing environments.