What is ETL Success Rate?
ETL Success Rate is the percentage of extract-transform-load jobs that complete successfully without error within a given period. It's a core reliability metric for any automated data pipeline, tracking how often the process of moving and reshaping data actually finishes cleanly.
TL;DR
ETL Success Rate is the percentage of data pipeline jobs that complete without error, a core reliability signal for automated data infrastructure.
Formula
ETL Success Rate = (Number of Successful ETL Job Runs / Total Number of ETL Job Runs) x 100
Why It Matters
ETL Success Rate matters because a failed ETL job doesn't just delay one report, it can silently break every downstream dashboard, model, or automated decision that depends on that data being current and complete. Because ETL processes typically run on a schedule without a human watching each run, a low or declining success rate is often the first measurable signal that something is wrong with a data pipeline, well before anyone notices stale or missing numbers in a report. Tracking this rate over time, and by individual job or source, also helps a data team distinguish between a one-off failure and a systemic reliability problem with a specific connector or transformation step. For any business that depends on automated daily refreshes, ETL success rate is one of the most fundamental trust signals underlying every other data metric downstream of it.
Example
A company runs 30 scheduled ETL jobs each night across its various data sources. Over the past week, 205 out of 210 total job runs completed successfully, while 5 failed due to a source API timeout. ETL Success Rate for the week is 205 divided by 210, times 100, which equals roughly 97.6%, prompting the data team to investigate the specific source responsible for the failures.
Frequently Asked Questions