No-Code/Low-Code Platforms for Scalable Data Engineering and Transformation

  • Authors

    • Dr. P. Bastin Thiyagaraj Assistant Professor, Department of IT, St. Joseph’s College (Autonomous), Tiruchirappalli, Tamil Nadu, India. Author

    Published 2026-01-01

  • No-Code Platforms, Low-Code Development, Data Engineering, Data Transformation, ETL/ELT, Data Pipeline Automation, Scalable Architecture, DataOps, Citizen Developers, Cloud-native Data Tools

    Issue

    Vol. 1 No. 1 (2026)

    Section

    Articles

    How to Cite

    [1]
    B. Thiyagaraj, “No-Code/Low-Code Platforms for Scalable Data Engineering and Transformation”, IJAIDT, vol. 1, no. 1, pp. 01–12, Jan. 2026, Accessed: Mar. 02, 2026. [Online]. Available: https://worldcometresearchgroup.com/index.php/ijaidt/article/view/65

  • Abstract

    In the era of big data, the ability to quickly ingest, process, and transform large volumes of data is essential for organizations seeking to gain insights and drive innovation. However, traditional data engineering practices often require advanced programming skills, which can create bottlenecks and limit agility. No-code and low-code platforms are emerging as powerful tools that democratize data engineering by enabling both technical and non-technical users to build scalable data pipelines, automate transformations, and manage complex workflows with minimal coding. This paper explores the evolution, architecture, capabilities, and limitations of no-code/low-code platforms for data engineering. It evaluates popular tools, compares them with traditional approaches, and discusses their role in cloud-native and hybrid data ecosystems. The paper also addresses scalability, integration, and governance challenges while presenting real-world case studies that illustrate their impact on business agility and time-to-insight.

  • References

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