Which of the following best describes the difference between ETL and ELT?

What is the primary role of the "Extract" phase in an ETL pipeline?

Which scenario is most appropriate for batch processing in a data pipeline?

Which component is typically responsible for applying business rules and data cleaning in an ETL pipeline?

In a typical ETL pipeline architecture, what is the function of the Loader?

Master the practical skills needed to design, build, and automate robust data pipelines using Python. This course covers ETL and ELT fundamentals, batch processing, incremental loading, and orchestration patterns, equipping you to handle real-world data engineering tasks with confidence.

Establish a solid understanding of ETL and ELT concepts, pipeline architecture, and the core components of data workflows.

Dive into practical methods for extracting data from various sources, including files, APIs, and databases.

Master the core transformation techniques and learn how to load processed data into various destinations.

Advance your skills with incremental loading, modularization, testing, logging, and orchestration patterns.

Quiz: ETL/ELT Fundamentals

1. Which of the following best describes the difference between ETL and ELT?

2. What is the primary role of the "Extract" phase in an ETL pipeline?

3. Which scenario is most appropriate for batch processing in a data pipeline?

4. Which component is typically responsible for applying business rules and data cleaning in an ETL pipeline?

5. In a typical ETL pipeline architecture, what is the function of the Loader?