5 Best Practices for Data Warehouse Development

July 16, 2019

Whether your organization is creating a new data warehouse from scratch or re-engineering a legacy warehouse system to take advantage of new capabilities, a handful of guidelines and best practices will help ensure your project’s success. These best practices for data warehouse development will increase the chance that all business stakeholders will derive greater value from the data warehouse you create, as well as lay the groundwork for a data warehouse that can grow and adapt as your business needs change. 

In this ebook, we discuss five best practices for data warehouse development, including:

  • Creating a highly effective data model 
  • Applying the agile approach to data warehouse development
  • Adopting a data warehouse automation tool, and more
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How Snowflake Automates Performance in a Modern Cloud Data Warehouse
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