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Introduction to Data Engineering on Databricks

• The Big Book of Data Engineering 2nd Edition offers a comprehensive guide to data engineering, covering topics such as performance tips, profile PySpark, low-latency streaming data pipelines, building geospatial data products, data lineage with Unity Catalog, easy ingestion to Lakehouse with COPY INTO, simplifying change data capture, and cross-government data sharing.
• The book also discusses the challenges of building complex data pipelines, such as repetitive data ingestion tasks, complex scalable infrastructure, reliable tools for orchestrating pipelines, low-latency data pipelines for real-time data, and constant focus on performance tuning.
• Databricks Lakehouse Platform offers an end-to-end solution for ingesting, transforming, processing, scheduling, and delivering data.
• It automates the complexity of building and maintaining pipelines and running ETL workloads directly on a data lake, allowing data engineers to focus on quality and reliability to drive valuable insights.
• Key differentiators for successful data engineering with Databricks include data ingestion at scale, scalable data pipelines, and a focus on enterprise-grade and enterprise-ready approaches.

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