This guide explores why traditional data warehouses and lakes fall short and introduces the data lakehouse as a unified architecture for Azure. It outlines warehouse limitations such as cost, vendor lock-in, and ETL complexity, and lake limitations including governance and performance issues. The lakehouse combines open storage like ADLS with ACID transactions and real-time processing to support BI, ETL, and data science use cases. The guide recommends best practices such as separation of compute and storage, open table formats like Apache Iceberg, federation across data sources, and robust security controls. It concludes by positioning Starburst Galaxy as a fully managed lakehouse solution for Azure.

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