SELF-HEALING DATA PIPELINES A FAULT-TOLERANT APPROACH TO ETL WORKFLOWS

As organizations adapt to using fresh data to base their choices, they need ETL tools that work flawlessly and fast.
However, while common ETL process’s function, they regularly deal with instances of data corruption, changes
in schema and infrastructure problems leading to operational problems and poor data quality. This article explains
why using self-healing pipelines is becoming a popular way to solve these challenges. Thanks to automation, selfhealing pipelines have the ability to notice faults, figure out the problems and respond quickly. The article
examines the key parts, advanced tools, ways to handle faults and everyday applications that show how selfhealing is transforming modern data engineering. The chapter ends by talking about the strengths, weaknesses
and likely future directions of this innovative approach to creating robust ETL workflows.