This guide shares five best practices for data warehouse development. First, create a clear, source-agnostic data model to document data relationships and support future growth. Second, adopt Agile methodologies like Scrum or Kanban to enable faster, iterative development. Third, favor ELT over ETL to save costs and improve traceability by transforming data inside the warehouse. Fourth, use automation tools to standardize and speed up coding, reducing errors and improving consistency. Finally, train teams on new approaches to ensure effective adoption. These practices help build scalable, adaptable data platforms that deliver long-term business value.

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