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 ...

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 ...

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

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 ...