Data warehousing is the pinnacle of business intelligence and reporting. For many, it is the start of their transformation into the space of data and analytics. As with all database implementations, a well-defined schema and data model are required to properly store the data in a way that supports data access patterns. As data warehouses grow in size and scope, their data model becomes important for maintainability and performance reasons. Depending on the needs of the business, each data model can have its use case, but might not survive the project in the long term. Moreover, cutting-edge technology such as a NoSQL database might not be considered in place of more traditional alternatives. An analysis of applicable data models and NoSQL database viability will be assessed in the realm of data warehousing. By converting Microsoft’s AdventureWork’s sample database to alternative data warehousing data models, we can study the differences between data models concerning storage, scalability, ease of use, and resilience to change.