When it comes to managing data in an organization, two terms that are often used interchangeably are business intelligence (BI) and data warehousing. However, it is important to understand that these are two separate disciplines with distinct focuses and purposes.

At a high level, the primary focus of a data warehouse is the production of data. A data warehouse is a centralized repository that stores large volumes of data from various sources. It is designed to support complex data integration processes and provide a reliable and consistent source of data for analysis and reporting.

On the other hand, the primary focus of BI is the consumption, presentation, and delivery of the data produced by the data warehouse. BI involves the use of tools and technologies to analyze and visualize data, enabling users to make informed business decisions based on the insights derived from the data.

One common misconception within the SQL Server community is the confusion between BI and data warehousing, as exemplified by the AdventureWorks samples available at the Microsoft SQL Server Community Projects & Samples site. These samples include an OLTP database, a data warehouse database, and a SQL Server Analysis Services (SSAS) database or cube. However, it is important to note that these samples are primarily focused on BI scenarios, where the emphasis is on data consumption rather than data production.

For instance, the AdventureWorks data warehouse is populated directly from Comma Separated Values (CSV) files, rather than through complex data integration processes. Therefore, these samples should be considered as business intelligence samples rather than data warehouse samples.

It is crucial to recognize that as a data warehouse matures, the focus shifts more towards data production. This is evident in the data warehouse maturity model, where the data warehouse team allocates increasing resources to data integration. With the growing complexity and volume of data, data warehousing becomes more about efficiently producing and managing data, while BI remains focused on consuming and presenting that data.

In conclusion, while business intelligence and data warehousing are related concepts, they serve different purposes within an organization. Data warehousing is primarily concerned with the production of data, while BI focuses on the consumption, presentation, and delivery of that data. Understanding this distinction is essential for organizations looking to effectively leverage their data assets and drive informed decision-making.

For more information on data warehousing and BI best practices, you can refer to the Microsoft EDW Architecture, Guidance, and Deployment Best Practices – Chapter 2: Data Architecture.