International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 2 (March-April 2025) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.

Integrated Snowflake with AWS and AWS ETL Migration

Author(s) Ankit Srivastava
Country United States
Abstract As more and more companies demand effective data management and analysis, they have turned to cloud options. In this research paper, we discuss Snowflake (a cloud-based data warehouse platform) integration with Amazon Web Services and data pipeline migration from Extract, Transform, and Load to AWS. Stacking Snowflake, a cloud-based data warehouse, with Amazon Web Services (AWS), is now the go-to solution for companies looking to automate data processing, analytics, and storage. This whitepaper covers the technical integration between Snowflake and AWS for the Extract, Transform, Load (ETL) migration of ETL workflows to AWS services. What are the main factors, issues and resolutions for smooth integration as well as best practices for ETL pipeline optimization in this ecosystem.
Keywords AWS, Snowflake, Datawarehouse, Data Pipeline, Cloud
Field Computer Applications
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-02-23
DOI https://doi.org/10.36948/ijfmr.2025.v07i01.37046
Short DOI https://doi.org/g854n3

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