Data Processing ETL and Data Transformation 3

Question 1

What is data lineage?

Accepted Answer

The ability to trace data's origin, movements, and transformations throughout its lifecycle

Answer

The chronological order of database backups

Answer

The number of rows added per ETL job

Answer

The version history of a stored procedure

Question 2

What is the purpose of a lookup transformation in ETL?

Accepted Answer

To retrieve related values from a reference table during transformation

Answer

To delete records that fail validation

Answer

To sort rows before loading into the target

Answer

To compress data files before transmission

Question 3

What is change data capture (CDC)?

Accepted Answer

A technique that identifies and captures only the changes made to source data since the last extraction

Answer

A method for compressing large ETL log files

Answer

A process for auditing user login attempts

Answer

A way to replicate an entire database nightly

Question 4

What does 'data flattening' mean in ETL transformation?

Accepted Answer

Converting hierarchical or nested data structures into a tabular row-column format

Answer

Reducing file sizes by removing whitespace

Answer

Splitting one record into multiple rows

Answer

Encrypting nested JSON objects

Question 5

Which scheduling approach runs ETL jobs at fixed time intervals regardless of data availability?

Accepted Answer

Time-based scheduling

Answer

Event-driven scheduling

Answer

Manual triggering

Answer

Continuous streaming

Question 6

What is data masking used for in ETL pipelines?

Accepted Answer

Protecting sensitive data by replacing it with realistic but fictitious values

Answer

Hiding database tables from unauthorized users

Answer

Compressing data during transfer

Answer

Encoding binary data into text format