European Journal of Computer Science and Information Technology (EJCSIT)

EA Journals

AI-Driven Innovation: Building Low-Code Data Pipelines for Real-Time Decision Making

Abstract

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.

Keywords: Real-time Analytics, artificial intelligence integration, data governance, federated development, low-code data pipelines

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This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

 

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Email ID: editor.ejcsit@ea-journals.org
Impact Factor: 7.80
Print ISSN: 2054-0957
Online ISSN: 2054-0965
DOI: https://doi.org/10.37745/ejcsit.2013

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