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AnalysisData engineering & the warehouse/lakehouseDatabricks
Databricks Blog · Read source ↗

The article discusses the advancements in automated change data capture (CDC) technologies, particularly in handling complex real-world scenarios using Spark. It highlights the challenges data engineers face in implementing CDC and the solutions being developed to address these issues.

MyDataWork POV — Auto CDC's evolution is a big deal, especially with Spark at the helm. The real breakthrough lies in addressing those challenging, real-world edge cases that typically hinder data engineers, rather than merely automating the process. By addressing these sticky situations, we're enhancing both the speed and intelligence of CDC. This shift could redefine how we handle data changes, moving from a reactive to a proactive approach. But let's not ignore the learning curve—engineers will need to adapt quickly.
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