May 13, 2022, 4:58 a.m. | Divyanshu Raj

Towards Data Science - Medium towardsdatascience.com

The architectural backbone to auto-scale in terms of infra and cost, based on the volume of data to be processed

Photo by Edward Howell on Unsplash

Building a data processing pipeline is one of the most common problem statements, for which you would have written small scripts or built a full-fledged scalable system based on the amount, and frequency of data. In this article, we will talk about the idea of event-driven scalability, the backbone that will be cost-optimized, and …

cost-optimization data data processing design systems event event-driven-architecture pipeline processing scalability

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Sr. VBI Developer II

@ Atos | Texas, US, 75093

Wealth Management - Data Analytics Intern/Co-op Fall 2024

@ Scotiabank | Toronto, ON, CA