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 ...

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 ...

SQL Server Integration Services (SSIS) is now officially supported in the latest SQL Server Management Studio (SSMS) 22 ...

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 ...

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 ...

ETL, according to the ETL definition, is nothing more than extraction, transformation, and loading of data. This is a critical step in data warehousing. An easy way to understand this is to look at ...

Data Integration vs ETL: What Are the Differences? Your email has been sent If you're considering using a data integration platform to build your ETL process, you may be confused by the terms data ...

Discover how data engineer Ravi Kiran builds self-healing, metadata-driven ETL pipelines that cut failures, automate schema ...

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 ...

Sachin is the CEO and Co-Founder of Dataworkz, which uses AI-powered automation to take the slog out of building a data-driven enterprise. This is the first in a series of articles about ELT, how it ...