Enhancing Data Integration and ETL Processes Using AWS Glue
Year: 2024
Type: article
Abstract: The rapid proliferation of data in modern enterprises necessitates advanced solutions for seamless integration and transformation. AWS Glue, a fully managed and serverless ETL (Extract, Transform, Load) service, emerges as a versatile tool for addressing the challenges of data integration, scalability, and real-time processing. This paper explores AWS Glue's architecture, features, and capabilities, highlighting its strengths and identifying areas for improvement. Comparative analyses with leading ETL tools and real-world use cases illustrate AWS Glue's potential in data lake formation, real-time analytics, and migration workflows. Additionally, the paper examines emerging trends and future directions in serverless ETL technologies, offering insights into their role in shaping enterprise strategies. By leveraging AWS Glue, organizations can establish efficient, cost-effective, and scalable data workflows, empowering them to extract actionable insights and maintain a competitive edge in data-driven ecosystems.
Authors: Pothineni, Balakrishna, Maruthavanan, Durgaraman, Gadi Parthi, Ashok, Jayabalan, Deepak, Veerapaneni, Prema kumar
Institution: JPMorgan Chase & Co (United States)
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6930803669