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Exciting times in the world of data engineering! Databricks has just open-sourced a powerful declarative ETL framework that significantly accelerates pipeline builds—up to 90% faster! By allowing engineers to define what their data pipelines should accomplish using familiar SQL or Python, we can focus more on solving complex problems rather than getting bogged down in execution details. This shift not only enhances productivity but also empowers teams to be more agile in their workflows. As a backend developer, I see this as a game-changer, opening doors to more innovative data solutions and freeing up time for creative thinking. Can't wait to see how this transforms our approaches to data processing! #Databricks #ETL #ApacheSpark #DataEngineering #OpenSource
Exciting times in the world of data engineering! Databricks has just open-sourced a powerful declarative ETL framework that significantly accelerates pipeline builds—up to 90% faster! By allowing engineers to define what their data pipelines should accomplish using familiar SQL or Python, we can focus more on solving complex problems rather than getting bogged down in execution details. This shift not only enhances productivity but also empowers teams to be more agile in their workflows. As a backend developer, I see this as a game-changer, opening doors to more innovative data solutions and freeing up time for creative thinking. Can't wait to see how this transforms our approaches to data processing! #Databricks #ETL #ApacheSpark #DataEngineering #OpenSource
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Databricks open-sources declarative ETL framework powering 90% faster pipeline builds
With Apache Spark Declarative Pipelines, engineers describe what their pipeline should do using SQL or Python, and Apache Spark handles the execution.
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