In Part 1, we focused on securely setting up the AWS Glue and Snowflake integration, including IAM roles, and Secrets Manager. Now it’s time to move towards the core functionality—building the actual ETL pipeline using AWS Glue Studio and connecting it to Snowflake!

In today’s modern data landscape, organizations rely on fast, secure, and automated pipelines to process and analyze data. Two major players that help achieve this are AWS Glue, a serverless ETL (Extract, Transform, Load) service from Amazon, and Snowflake, a highly scalable and cloud-native data warehouse.

Regression testing is an essential part of any software development cycle. As your project grows, manual testing becomes repetitive, time-consuming, and error-prone. That’s where automation comes in. In this blog, I’ll walk you through how I automated my web application’s regression testing using Selenium with Python, all inside Visual Studio Code.

In today’s data-driven world, businesses need a structured approach to managing and processing vast amounts of data. This is where ETL (Extract, Transform, Load) processes come into play. ETL helps organizations systematically collect, refine, and store data for further analysis and decision-making.

Introduction Performance optimization is crucial in React applications, especially when

Introduction In the world of modern data, logs are the