Home
World Journal of Advanced Engineering Technology and Sciences
International, Peer reviewed, Referred, Open access | ISSN Approved Journal

Main navigation

  • Home
    • Journal Information
    • Abstracting and Indexing
    • Editorial Board Members
    • Reviewer Panel
    • Journal Policies
    • WJAETS CrossMark Policy
    • Publication Ethics
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Issue in Progress
    • Current Issue
    • Past Issues
    • Become a Reviewer panel member
    • Join as Editorial Board Member
  • Contact us
  • Downloads

ISSN: 2582-8266 (Online)  || UGC Compliant Journal || Google Indexed || Impact Factor: 9.48 || Crossref DOI

Fast Publication within 2 days || Low Article Processing charges || Peer reviewed and Referred Journal

Research and review articles are invited for publication in Volume 18, Issue 2 (February 2026).... Submit articles

End-to-end data pipeline automation using AWS S3, Redshift and SQL

Breadcrumb

  • Home
  • End-to-end data pipeline automation using AWS S3, Redshift and SQL

Peeyush Patel *

Oklahoma State University, Stillwater, OK, USA.

Review Article

World Journal of Advanced Engineering Technology and Sciences, 2025, 17(01), 303–313

Article DOI: 10.30574/wjaets.2025.17.1.1403

DOI url: https://doi.org/10.30574/wjaets.2025.17.1.1403

Received on 30 August 2025; revised on 13 October 2025; accepted on 16 October 2025

The modern business ought to have automated data pipelines to manage, process, and analyze big data. AWS S3 and Redshift are cloud-native products that offer infrastructures of scalable, cost-effective, and secure end-to-end pipelines. The architecture and workflow of automated pipelines are reviewed with particular attention to the data ingestion, storage, and data transformation and querying in SQL, the orchestration, monitoring, and optimization strategies. Automation allows organizations to reduce the amount of manual processing, enhance the availability of data, and enhance the capabilities of analytical tools. The paper also discusses the problem of vendor lock-in, compliance, and skills gaps, and provides the future outlook of machine learning-based optimization and multi-cloud interoperability. Cloud-native automated pipelines thus remain on the leading edge in supporting real-time visibility and keeping the enterprise competitive in the digital era.

Data Pipeline; AWS S3; Redshift; SQL; Automation

https://wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2025-1403.pdf

Preview Article PDF

Peeyush Patel. End-to-end data pipeline automation using AWS S3, Redshift and SQL. World Journal of Advanced Engineering Technology and Sciences, 2025, 17(01), 303-313. Article DOI: https://doi.org/10.30574/wjaets.2025.17.1.1403.

Get Certificates

Get Publication Certificate

Download LoA

Check Corssref DOI details

Issue details

Issue Cover Page

Editorial Board

Table of content


Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


Copyright © 2026 World Journal of Advanced Engineering Technology and Sciences

Developed & Designed by VS Infosolution