Automated ETL Intelligence: Metadata-Orchestrated Framework with Rule-Based Heuristics for Monitoring and Reporting

Authors

  • Srinubabu Kilaru Author

DOI:

https://doi.org/10.48047/ijiee.2013.3.6.9

Keywords:

Metadata-driven ETL, AI heuristics, PL/SQL ETL engine, execution monitoring, anomaly detection, ETL dashboards, data integration, SQL Server, Oracle, IEEE 11179, rule-based alerting.

Abstract

In the era of large-scale data ecosystems, ensuring adaptability, transparency, and operational intelligence in ETL (Extract, Transform, Load) pipelines is paramount. This paper introduces a metadata-driven, SQL-native ETL orchestration framework designed to automate data integration tasks while embedding observability and anomaly detection capabilities directly

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Published

20.07.2013

Issue

Vol. 3 No. 6 (2013): Volume 3 issue 6 (2013)

Section

Articles

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How to Cite

Automated ETL Intelligence: Metadata-Orchestrated Framework with Rule-Based Heuristics for Monitoring and Reporting . (2013). International Journal of Information and Electronics Engineering, 3(6), 648-661. https://doi.org/10.48047/ijiee.2013.3.6.9