What Is a Virtual Warehouse?

A virtual warehouse is another term for a data warehouse. A data warehouse is a computing tool designed to simplify decision-making in business management. It collects and displays business data relating to a specific moment in time, creating a snapshot of the condition of the business at that moment. Virtual warehouses often collect data from a wide variety of sources.

A virtual warehouse is essentially a business database. The data found in a virtual warehouse is usually copied from multiple sources throughout a production system. This is done so related data can be searched quickly and without accessing the entire system. Performing a search of an entire production system at one time could potentially compromise the system's performance. Using a data warehouse removes this operating risk and speeds up the overall access process.

Depending on the type of information being stored in a virtual warehouse, a single warehouse can become overburdened with data from dozens of different sources relating to any number of potential topics. To prevent the warehouse from becoming impossible to navigate, subdivisions called data marts are sometimes used. These data marts divide the information saved in the warehouse into categories that can be individually selected and searched based on what the user is seeking.

Data warehouses are generally updated regularly to ensure they reflect the current condition of the business whose data they store. They can often be set to update on a daily, weekly or customized timetable, depending on the desires of the user. The data stored in a virtual warehouse is static. This means new data is stored alongside existing data rather than over it, allowing you to access historical information as well as current information.

Another advantage to using a virtual warehouse to store and catalog data is integration. In computing terms, integration is when data pulled from two or more sources that label their information differently is stored using a single means of identification. Integration is useful for data retrieval purposes, because it makes it possible to search all stored data at one time, as opposed to performing individual searches of each source dictated by the source's specific identification method.