This is one of the most used technologies for dealing with the huge amount of data in companies. It is necessary because
today´s digital events are multidimensional. In the former analog world, a purchase event would be recorded as, “Product X was purchased for Y dollars”. In today´s digital world, that same purchase event might include ten additional attributes or dimensions including things like the following: time of day, day of week, purchaser name, discount level, product packaging, product promotion, color, style, stock location, salesperson name, and a listing of all other products in the purchaser’s market basket. Every digital event has the ability to be recorder with dozens of other attributes or dimensions that can shed additional light on the event itself (Golfarelli y Rizzi, 2009).
This implies that information has to be available in a single location to be rapidly correlated and effectively analyzed for decision making. This location is the data warehouse.
Data warehouse is a repository for “historical, integrated, and consistent data” (Golfarelli y Rizzi, 2009), and it is based in the process known as ETL (Extract, Transform, Load). Data warehouses are “currently well established within several medium to large organizations, and it’s widely acknowledged that they paly a strategic role when it comes to providing end-users with easy access to key information that would otherwise be hardly available” (Golfarelli y Rizzi, 2009). For that reason, a data warehouse is a basic technology for the implementation of solutions related to information analysis, as Business Intelligence and Business Process Management, and it’s a part of what is known as supporting decision making systems.