Databricks Certified Data Engineer Associate ETL with Spark SQL 2

Question 1

Which metric best measures ETL with Spark SQL effectiveness?

Accepted Answer

Domain-specific KPIs aligned with defined objectives

Answer

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?

Accepted Answer

Through controlled processes that assess impact before changes

Answer

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?

Accepted Answer

Policies, procedures, guidelines, and records of decisions

Answer

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?

Accepted Answer

Through regular assessment, feedback loops, and iterative enhancement

Answer

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?

Accepted Answer

ETL with Spark SQL includes security considerations as an integral component

Answer

Security is an integral part of ETL with Spark SQL, ensuring that implementations are protected and compliant.

Databricks Data Engineer Practice Test