Optimizing Data Pipelines with AI and ML: Automation, Scalability, and Real-Time Analytics

Authors

  • Bujjibabu Katta

Keywords:

Artificial intelligence, machine learning, data pipelines, edge computing, anomaly detection

Abstract

The exponential growth of global data generation has fundamentally transformed data engineeringlandscapes, necessitating revolutionary approaches to pipeline architectures and processing methodologies.

References

David Reinsel, John Gantz, and John Rydning, "The Digitization of the World From Edge to Core,"

IDC Data Age Report, Seagate Technology, 2020. Available: https://www.seagate.com/files/www

content/our-story/trends/files/dataage-idc-report-final.pdf

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Published

2025-11-28

How to Cite

Bujjibabu Katta. (2025). Optimizing Data Pipelines with AI and ML: Automation, Scalability, and Real-Time Analytics . Journal of Computational Analysis and Applications (JoCAAA), 34(11), 915–927. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4265

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.