It’s hard to imagine data warehousing without ETL (extract, transformation, and load). For decades, analysts and engineers have embraced no-code ETL solutions for increased maintainability. Does this ...

Microsoft has dabbled in the ETL (extract-transform-load) marketplace for a long time, in fact, almost 2 decades. Way back in the day, SQL Server shipped with a command-line tool known as the Bulk ...

BlazingSQL builds on RAPIDS to distribute SQL query execution across GPU clusters, delivering the ETL for an all-GPU data science workflow. BlazingSQL is a GPU-accelerated SQL engine built on top of ...

This project implements a three-layer ETL (Extract, Transform, Load) pipeline for a data warehouse using SQL Server. The pipeline processes CRM and ERP data through Bronze (raw data), Silver (cleaned ...

Global software house Microsoft is making big data the focus of SQL Server 2019, set for release later this year. A key part is data virtualisation, eliminating complex ETL processes. Microsoft says ...

Data Ingestion vs. ETL: What Are the Main Differences? Your email has been sent Data ingestion and ETL are often used interchangeably. But, they're not the same thing. Here's what they mean and how ...

Amazon made a couple of announcements today at AWS re:Invent in Las Vegas that helps move data management toward a future without the need for extract transform load, or ETL. ETL is the bane of every ...

Project Overview This project analyzes the Netflix Titles Dataset to uncover insights about content trends, production countries, and genres. The dataset was extracted using the Kaggle API, cleaned ...