Databricks Certified Data Engineer Associate ETL with Spark SQL 2 — Questions and Answers
Question 1: Which metric best measures ETL with Spark SQL effectiveness?
- Domain-specific KPIs aligned with defined objectives (Correct answer)
- Number of meetings held about the topic
- Amount of documentation produced
- Budget spent on related tools
Correct answer: Domain-specific KPIs aligned with defined objectives
Effectiveness of ETL with Spark SQL is best measured through KPIs that align with defined objectives.
Question 2: How does ETL with Spark SQL handle change management?
- Through controlled processes that assess impact before changes (Correct answer)
- Changes are not allowed once implemented
- All changes happen immediately without review
- Change management is handled separately
Correct answer: Through controlled processes that assess impact before changes
Changes to ETL with Spark SQL should follow controlled processes with proper impact assessment.
Question 3: What documentation is essential for ETL with Spark SQL?
- Policies, procedures, guidelines, and records of decisions (Correct answer)
- No documentation is needed
- Only a one-page summary document
- Only informal email notes
Correct answer: Policies, procedures, guidelines, and records of decisions
Essential ETL with Spark SQL documentation includes policies, procedures, guidelines, and decision records.
Question 4: How does ETL with Spark SQL contribute to continuous improvement?
- Through regular assessment, feedback loops, and iterative enhancement (Correct answer)
- By maintaining the status quo indefinitely
- By preventing any changes to existing processes
- Through one-time implementation only
Correct answer: Through regular assessment, feedback loops, and iterative enhancement
Continuous improvement in ETL with Spark SQL comes from regular assessment and iterative enhancement cycles.
Question 5: What is the relationship between ETL with Spark SQL and security?
- ETL with Spark SQL includes security considerations as an integral component (Correct answer)
- Security is completely unrelated to this topic
- ETL with Spark SQL replaces all other security measures
- Security only applies to network-related topics
Correct 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.
Question 6: How should ETL with Spark SQL be prioritized against competing organizational needs?
- Based on risk assessment and business impact analysis (Correct answer)
- Always given highest priority over everything else
- Always given lowest priority
- Prioritized randomly without analysis
Correct answer: Based on risk assessment and business impact analysis
Prioritization of ETL with Spark SQL should be based on risk assessment and business impact.
Databricks Certified Data Engineer Associate ETL with Spark SQL 2
Which metric best measures ETL with Spark SQL effectiveness?