Dive Deeper into Data Engineering on Databricks

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To derive value from data, engineers need to collect, transform, and orchestrate data from various data types and source systems. However, today’s data engineering solutions support only a limited number of delivery styles, involve a significant amount of hand-coding, and have become resource-intensive. Modern data engineering requires more advanced data lifecycle for data ingestion, transformation, and processing. In this session, learn how the Databricks Lakehouse Platform provides an end-to-end data engineering solution — ingestion, processing and scheduling — that automates the complexity of building and maintaining pipelines and running ETL workloads directly on a data lake, so your team can focus on quality and reliability to drive valuable insights.

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Great explanation of delta live tables.

my_j.a.r.v.i.s.
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Rivian dude, did he even say thank you to the presenter before him? 😂

toulasantha
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