A data engineer is building a pipeline to ingest unstructured and semi$-$structured data. A data scientist will explore the data for potential use in an ML solution.

Which ingestion approach is best for this business need?

Group of answer choices

Use an extract, load, and transform $($ELT$)$ approach and load the nearly raw data into an S$3$ data lake.

Use an extract, transform, and load $($ETL$)$ approach and load the highly transformed data into an S$3$ data lake.

Use an extract, transform, and load $($ETL$)$ approach and load the highly transformed data into an Amazon Redshift data warehouse.

Use an extract, load, and transform $($ELT$)$ approach and load the minimally transformed data into an Amazon Redshift data warehouse