An end-to-end data warehousing project that ingests raw source data, cleans and transforms it through a layered architecture, and models it into a star schema ready for analytics and BI reporting.

The Fastest On-Ramp Into Data CareersData roles pay a premium — data engineers and analysts consistently rank among the ...

This repository contains a documentation tutorial on how to ETL a sample population survey data to an OMOP database instance Inspired by Cookie Cutter Data Science. ├── 1.OHDS Tools Installation │ ├── ...

This course teaches how to build production-ready ETL pipelines using pure SQL on the Databricks Data Intelligence Platform. Students learn Streaming Tables with Auto Loader for incremental ingestion, ...

Presenting new capabilities for Fabric, Power BI, OneLake, and Azure SQL, the company took the stage in Barcelona to outline ...

New Progress Domo release helps organizations deliver trusted data and AI outcomes faster with greater pipeline visibility, governed AI ...

For those who want to verify their ability to choose services and settings based on requirements through 100 four-choice ...

ETL isn't dead, but AI demands smarter pipelines. Learn how observability, anomaly detection, lineage, and self-healing improve data reliability.

Vision Board EdTech, a career-focused training platform for Azure Data Engineering and Generative AI, reports that about | ...

Amazon Web Services (AWS) announced on September 30, 2026, that it has embedded the open-source analytics engine DuckDB into Amazon Aurora ...

AWS Database Migration Service AWS DMS was originally designed for a specific task: lifting relational databases off on-premises servers and moving them into managed Amazon ...