Beyond ETL: Orchestrating End-to-End Data Products with Modern Automation Frameworks

Authors: Ramesh Betha

DOI: https://doi.org/10.5281/zenodo.15084298

Short DOI: https://doi.org/g89sbc

Country: United States

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Abstract: The traditional Extract, Transform, Load (ETL) paradigm that has governed data integration for decades is rapidly becoming insufficient for modern enterprise data needs. As organizations transition from siloed data management to comprehensive data products, there exists a critical need for orchestration capabilities that transcend basic ETL functionality. This paper examines the evolution from ETL-centric approaches to holistic data product orchestration, evaluates emerging automation frameworks that facilitate this transition, and proposes an architecture for end-to-end data product lifecycle management. Through case studies and empirical analysis, we demonstrate how modern orchestration frameworks can reduce time-to-value by up to 70% while improving data quality, governance, and operational resilience. The findings suggest that organizations embracing these orchestration paradigms achieve significantly higher returns on their data investments and greater agility in adapting to changing business requirements.

Keywords: Data orchestration, Data products, ETL automation, Data mesh, DataOps, MLOps, Data engineering, Real-time analytics

Paper Id: 232298

Published On: 2024-05-24

Published In: Volume 12, Issue 3, May-June 2024

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