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, changesin schema and infrastructure problems leading to operational problems and poor data quality. This article explainswhy 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 articleexamines 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, weaknessesand likely future directions of this innovative approach to creating robust ETL workflows.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-07
DOI
https://doi.org/10.5281/zenodo.15615305
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Big Data and Business Intelligence
article

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

article en

Abstract

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, changesin schema and infrastructure problems leading to operational problems and poor data quality. This article explainswhy 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 articleexamines 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, weaknessesand likely future directions of this innovative approach to creating robust ETL workflows.

Zenodo (CERN European Organization for Nuclear Research)
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