ELT vs. ETL: What's the difference?

This is a podcast episode titled, ELT vs. ETL: What's the difference?. The summary for this episode is: <p>This episode of <em>Techsplainers</em> compares two fundamental data integration approaches: ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform). We break down how these similar-sounding acronyms represent significantly different data processing workflows. ETL, the traditional approach dating back to the 1970s, extracts data from sources, transforms it in a staging area, and then loads clean data into the target system—prioritizing data quality and structure. In contrast, ELT first loads raw data directly into the target system before transforming it there, leveraging the processing power of modern data warehouses for faster implementation and real-time capabilities. The episode explores the benefits and ideal use cases for each method, helping listeners understand when to apply ETL for carefully synchronized data integration versus when ELT might better serve high-volume, real-time data needs.&nbsp;</p><p><br></p><p>Find more information at <a href="https://www.ibm.com/think/topics/elt-vs-etl" rel="noopener noreferrer" target="_blank">https://www.ibm.com/think/topics/elt-vs-etl</a></p><p>Find more episodes at <a href="https://www.ibm.biz/techsplainers-podcast" rel="noopener noreferrer" target="_blank">https://www.ibm.biz/techsplainers-podcast</a></p><p><br></p><p><strong>Narrated by Matt Finio&nbsp;</strong></p>