Data Quality in an ETL Process — Catching Technical and Business Errors Before They Reach the Target System
A single value that cannot be converted — a date in the wrong format, a number with the wrong decimal separator — and the entire ETL run aborts. Data quality in an ETL process means catching such errors proactively: identifying, logging and isolating them before they reach the target system. This article is the entry point to … Read more