What is the difference between ETL and ETL?

Overview In the data engineering lifecycle, various data integration processes are used to make sense of this data. In this article, we'll focus on the two popular approaches: ETL and ELT . But first, a few definitions: Data Ingestion: This is the process of moving data from source systems into storage or simply, data movement from point A to point B. Data Integration: This process combines data from multiple source into a coherent format that is ready for analytics or decision making Data Pipeline: This is any combination of systems and processes that move data through the stages of the data engineering lifecycle eg ETL Pipeline(extracts raw data from an API using a Python scipt -> transforms data with dbt -> loads transformed data into a storage database) Data lakes: These are special kinds of data stores that, unlike data warehouses, accept any kind of structured or unstructured data without transformation. Now that we are all caught up on the definitions, let's look at ETL. ETL ETL