AI-Driven Innovation: Building Low-Code Data Pipelines for Real-Time Decision Making
Low-code data pipelines enhanced by artificial intelligence represent a transformative shift in enterprise data engineering and analytics. The integration of AI within these platforms has democratized data pipeline development, enabling business analysts and citizen developers to perform complex dat...
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| Published in | European Journal of Computer Science and Information Technology Vol. 13; no. 49; pp. 57 - 75 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
26.06.2025
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| Online Access | Get full text |
| ISSN | 2054-0957 2054-0965 |
| DOI | 10.37745/ejcsit.2013/vol13n495775 |
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| Summary: | Low-code data pipelines enhanced by artificial intelligence represent a transformative shift in enterprise data engineering and analytics. The integration of AI within these platforms has democratized data pipeline development, enabling business analysts and citizen developers to perform complex data integration tasks. Modern tools and platforms have revolutionized how organizations build and maintain scalable data pipelines, leading to improved efficiency, reduced costs, and accelerated deployment cycles. The adoption of federated development models, coupled with robust governance frameworks and best practices, has enabled organizations to maintain data quality while fostering innovation across distributed teams. This technological evolution has fundamentally changed how enterprises approach data management, making real-time decision-making capabilities accessible across organizations while maintaining security and compliance standards. |
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| ISSN: | 2054-0957 2054-0965 |
| DOI: | 10.37745/ejcsit.2013/vol13n495775 |