International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064




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Informative Article | Data & Knowledge Engineering | India | Volume 12 Issue 2, February 2023 | Rating: 4.3 / 10


Adopting Low - Code Platforms for Data Pipeline Development in Cloud Environments

Chandrakanth Lekkala [5]


Abstract: The data explosion and the complexity of data integration in cloud settings have brought quite complex challenges to organizations. Typical data pipeline construction is often done manually, making the process time - consuming, skilled labour - intensive, and prone to errors. Low - code platforms have proven to be a transformative solution to deal with these challenges, as they enable faster development with fewer errors and more broadly encompass data integration abilities. The article scrutinizes low - code platforms under the provision of cloud environments and as a means of building and controlling data pipelines. It analyses the means through which these platforms can bring about faster development, facilitate data integration, and reduce the obstacles to access these platforms may pose to organizations. The article highlights the main characteristics of low code, including visual interface, already - built integrators, automated testing and deployment, and expandability. It can demonstrate real - world scenarios of deployment of a low - code platform by a wide range of industries, and it can identify the risks and concerns along the way. Additionally, this article provides recommendations to organizations that want to use low - code platforms in data pipeline building, and it lays out potential future studies in this area. With the adoption of low - code platforms, organizations can unleash the power of data assets, thus providing agility and a competitive edge for the organization in the time of big data and cloud computing era.


Keywords: Platforms of low coding, data pipelines, cloud computing, data integration, visual development, automation, scalability, big data, cloud environments, data management


Edition: Volume 12 Issue 2, February 2023,


Pages: 1730 - 1736



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