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
Which metric best measures ETL with Spark SQL effectiveness?
Answer: Domain-specific KPIs aligned with defined objectives
Effectiveness of ETL with Spark SQL is best measured through KPIs that align with defined objectives.
How does ETL with Spark SQL handle change management?
Answer: Through controlled processes that assess impact before changes
Changes to ETL with Spark SQL should follow controlled processes with proper impact assessment.
What documentation is essential for ETL with Spark SQL?
Answer: Policies, procedures, guidelines, and records of decisions
Essential ETL with Spark SQL documentation includes policies, procedures, guidelines, and decision records.
How does ETL with Spark SQL contribute to continuous improvement?
Answer: Through regular assessment, feedback loops, and iterative enhancement
Continuous improvement in ETL with Spark SQL comes from regular assessment and iterative enhancement cycles.
What is the relationship between ETL with Spark SQL and security?
Answer: ETL with Spark SQL includes security considerations as an integral component
Security is an integral part of ETL with Spark SQL, ensuring that implementations are protected and compliant.
How should ETL with Spark SQL be prioritized against competing organizational needs?
Answer: Based on risk assessment and business impact analysis
Prioritization of ETL with Spark SQL should be based on risk assessment and business impact.