Reinforcement Learning for Adaptive ETL Scheduling in Data Warehouses

Authors

  • Anshul Verma

Keywords:

Reinforcement Learning, ETL Scheduling, Data Warehousing, Resource Allocation, Cloud Computing, Policy Optimization

Abstract

Extract-Transform-Load employment of job scheduling in large-scale data warehousing systemscontinues to face persistent challenges due to the limitations of fixed, rule-based orchestration models that are incapable of optimizing

References

Abhishek Verma et al., "Large-scale cluster management at Google with Borg," ACM, 2015. [Online].

Available: https://dl.acm.org/doi/pdf/10.1145/2741948.2741964

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Published

2025-11-13

How to Cite

Anshul Verma. (2025). Reinforcement Learning for Adaptive ETL Scheduling in Data Warehouses . Journal of Computational Analysis and Applications (JoCAAA), 34(11), 249–264. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4121

Issue

Vol. 34 No. 11 (2025): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.