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 ...

ETL (Extraction, Transformation, and Loading) in SQL Server is especially useful when data from the source systems does not conform to the business rules. Before loading all the data captured into a ...

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 ...

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 ...

BlazingSQL builds on RAPIDS to distribute SQL query execution across GPU clusters, delivering the ETL for an all-GPU data science workflow.

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 ...

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.