Check out this comprehensive article on ETL process.
ETL (Extract Transform Load) process:
- ETL is a popular batch processing pattern used in data engineering to collect and store data
- It consists of three stages: extract, transform, and load
- In the extract stage, data is retrieved from its original sources such as databases, websites, APIs, and more
- The staging area is a temporary location where the collected data is stored
- In the transform stage, the data is cleaned, formatted, and transformed to make it uniform and easier to handle
- The load stage involves moving the transformed data to its final destination, such as a Data Warehouse or repository
- A logging system is important to keep track of the progress of each stage and any potential errors
- ETL has become popular due to the availability of Cloud Storage and Database as Services (DBaaS) for high scalability and fault tolerance
- Advanced ETL/ELT processes use tools like Apache Spark, Apache Kafka, and Apache Airflow for better performance and efficiency.
Here’s the link to the full article: A gentle introduction to an ETL process | by Horacio Soldman | Dev Genius