Bifrost : No-Code ETL Tool


연구 분야: Databases



학회: 2024 3rd International Conference for Innovation in Technology (INOCON)


초록

In today’s world where mobile and web application usage is ubiquitous, a notable increase in data generation demands skilled management in order for organizations to expand. In this data-driven environment, Extract, Transform, Load (ETL) procedures play a crucial role in coordinating the smooth flow of data from various sources to analytics systems. Businesses use enterprise data lifecycle management (ETL) pipelines to extract data from a variety of sources, such as cloud computing and databases (SQL/NoSQL), which contain structured, semi-structured, and unstructured data in a variety of formats. After that, the data is transformed to match destination schemas, like cloud storage and data warehouses, where it is kept for analysis. But creating these ETL pipelines from scratch for every application takes a significant amount of time and money. This research study presents a brand-new no-code ETL tool with an easy-to-use drag-and-drop pipeline creation interface in order to solve this problem. To create a data flow that is efficient from source to destination, users can design pipelines with ease by choosing sources, defining necessary transformations, defining targets, and connecting these elements. In addition to streamlining pipeline development, the suggested system makes effective planning and storing for later use easier. This makes it an affordable and time-saving solution for businesses navigating the complexities of data management in the ever-evolving world of technology.


Author Profile
Suyog Sachin Shah

Department of Computer Engineering Bharatiya Vidya Bhavan’s Sardar Patel Institute of Technology (SPIT) Mumbai India

India
Author Profile
Varun Vasant Koranne

Department of Computer Engineering Bharatiya Vidya Bhavan’s Sardar Patel Institute of Technology (SPIT) Mumbai India

India
Author Profile
Khan Noman Asrar Ahmed

Department of Computer Engineering Bharatiya Vidya Bhavan’s Sardar Patel Institute of Technology (SPIT) Mumbai India

India

📄 논문 정보

발행 연도 2024년
인용수 151
출판 국가 India
사이트 IEEE
좋아요 수 0

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