Why are organizations adopting SQL data lakehouses? The SQL data lake house is a type of cloud data architecture that queries object stores at high speed and provides access to data across multiple sources to support both business intelligence (BI) and data science workloads. Enterprises adopt the SQL data lakehouse to streamline their architectures, reduce cost, and simplify data governance. Common use cases include reporting and dashboards, ad-hoc queries, 360-degree customer views, and artificial intelligence/machine learning (AI/ML).
This report explores the architectural components that make the SQL data lakehouse unified, simple, accessible, fast, economic, governed, and open. These components span the object store, a data layer, processing layer, semantic layer, communication layer, and client layer. Data teams that select the right components for their environments and establish the right points of integration can modernize their data architecture for analytics and BI.