Data & Databases
ETL
Extract, transform, load
A data pipeline pattern that extracts data, transforms it, and loads it into a destination.
Example
A nightly ETL job extracts transactions, cleans them, and loads reporting tables.
Why it matters
It prepares source records for consistent use in the destination.
You'll hear it
“We clean the records before they enter the reporting system.”
Can you control it?
Set by the team
The people building or running the AI choose this setup. An everyday user generally needs their help to change how this part works.
Common questions
- Can a failed load leave incomplete results?
- Yes. The process needs a way to recognize and recover from partial work.
- Does transforming data always preserve every detail?
- No. Some changes remove or combine information.
- Can changed source fields break the process?
- Yes. A new format may no longer fit the expected preparation rules.