ETL Testing ETL Data Extraction Techniques 2

Question 1

In ETL testing, what is the purpose of a 'source-to-staging' validation?

Accepted Answer

Confirm that raw extracted data landed intact in the staging area

Answer

Source-to-staging validation ensures that data extracted from the source arrived in the staging zone without corruption or loss.

Question 2

A trigger-based extraction fires a database trigger on DML events. What is a key risk of this approach?

Accepted Answer

It adds performance overhead to the source system

Answer

Trigger-based extraction executes additional logic on every insert, update, or delete, which can slow down the source system under heavy transactional load.

Question 3

What is 'push extraction' in ETL architecture?

Accepted Answer

The source system sends data to the ETL layer when changes occur

Answer

In push extraction, the source system proactively delivers changed data to the ETL pipeline, often via messaging queues or event streams.

Question 4

During ETL extraction testing, you notice the extracted file has fewer rows than the source query returns. What is the FIRST diagnostic step?

Accepted Answer

Check for extraction filters or WHERE clause conditions applied during pull

Answer

Extraction filters in the ETL configuration can silently limit rows, so verifying the extraction query or filter logic is the first step when row counts don't match.

Question 5

Which data extraction method is BEST for near-real-time ETL pipelines that need sub-minute latency?

Accepted Answer

Streaming CDC via Kafka or similar messaging

Answer

Streaming CDC publishes change events to a message broker in real time, enabling near-instant ingestion into downstream systems.

ETL Testing - extract, transform, load Practice Test

ETL Testing - extract, transform, load Practice Test

ETL Testing ETL Data Extraction Techniques 2