Understanding ETL | 39 | Matt Palmer | O'Reilly Media, Inc |
Extract, transform, load (ETL) is at the center of every application of data, from business intelligence to AI. This technical guide offers data engineers, engineering managers, and architects an overview of the modern ETL process, along with the challenges you're likely to face and the strategic patterns that will help you overcome them. You will be equipped to make informed decisions when implementing ETL and choose the technology stack that will help you succeed.
"Extract, transform, load" (ETL) is at the center of every application of data, from business intelligence to AI. Recent shifts in the data landscape-including the emergence of lakehouse architectures and the rising importance of high-scale real-time data-mean that today's data practitioners must approach ETL a bit differently.
This technical guide offers data engineers, engineering managers, and architects an overview of the modern ETL process, along with the challenges you're likely to face and the strategic patterns that will help you overcome them. You will be equipped to make informed decisions when implementing ETL and choose the technology stack that will help you succeed.
Discover what ETL looks like in the new world of data lakehouses
Learn how to deal with real-time data
Explore low-code ETL tools
Understand how to best achieve scale, performance, and observability
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