Srinubabu Kilaru said Bringing version control and CI/CD into data pipelines changed how quickly we could respond to policy ...

Remote work and high salaries can go hand in hand. Many professionals, especially those with sought-after credentials and experience, earn top dollar in high-paying remote jobs that offer more ...

In a detailed engineering post, Yelp shared how it built a scalable and cost-efficient pipeline for processing Amazon S3 ...

Abstract: This paper studies and analyzes how to optimize the ETL (Extract, Transform, and Load) process of the main structure quality inspection data of prefabricated concrete buildings under the ...

Abstract: Software testing is a crucial phase in the software development lifecycle, yet it often becomes a challenging task for engineers who must ensure comprehensive test coverage. While python ...

As the volume, velocity, and variety of data continue to accelerate, developers are facing a critical shift: data is no longer just stored and queried--it's constantly on the move. From traditional ...

A metadata-driven ETL framework using Azure Data Factory boosts scalability, flexibility, and security in integrating diverse data sources with minimal rework. In today’s data-driven landscape, ...

Today, at its annual Data + AI Summit, Databricks announced that it is open-sourcing its core declarative ETL framework as Apache Spark Declarative Pipelines, making it available to the entire Apache ...

A robust ETL (Extract, Transform, Load) pipeline for migrating data from Azure SQL Server to PostgreSQL, ensuring complete data transfer with proper validation and reporting. python -m src.main ...

This repository contains Python scripts for real-time ETL process from Excel files. It provides live updates and transformations to enhance data accuracy and efficiency.