The objective of this guide was to provide a roadmap to navigating cloud data warehouses, an essential part of the modern data stack. We also covered various concepts relevant to data warehouses, such as data modeling, SQL, and data engineering. 

Cloud data warehouses have significantly reduced or eliminated the need to pre-provision infrastructure to address analytical needs. The operational overhead associated with on-premises hardware and software upgrades, data backups, high availability, scaling, and monitoring is significantly reduced with cloud data warehouses and the tools available today. 

Additionally, the consumption-based cost model and elasticity of the cloud eliminate the need for the large capital investments required to launch a comprehensive analytics stack. 

While the convenience of the cloud has been a boon, it is important to evaluate the cost model, performance profile, availability, scalability, and efficiency of various offerings to ensure the right fit for your business’s analytics workloads.

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