A business data warehouse is a computer operating system used by companies to organize their information. Raw data is entered into the system, is processed and then made available to certain individuals within the company. Such data is used to analyze business performance and to make the company more effective in the future.
Storage is the primary function of a business data warehouse. It is, however, different from a data store. Over the course of the 20th century and into the 21st, companies began gathering larger and larger amounts of data. This comes from decades of sales, promotions and surveys. The business data warehouse is a solution for handling large amounts of information.
There are three stages involved in the data storage process. The first concerns the raw data compiled for developers and is called staging. The second, called integration, puts the data together. This involves cleaning, organizing, cataloging and some format changing. The final stage, access, presents the information for all users. By changing formats, it ensures compatibility for all files stored in the business data warehouse.
The warehouse itself is split into four layers. The operational database layer represents the raw source data imputed into the database. The tools used to search and make the data accessible are held within the data access layer. The data is organized into dictionaries in the metadata layer. Users encounter the final layer, the informational access layer, when they log onto the system.
Business data warehouse storage is considered good for creating a common information model. It not only helps storage, but also helps companies find inconsistencies in their data. The information itself, once processed, provides a wealth of possibilities. These include online analytical processing (OLAP) and data mining.
OLAP is a form of business intelligence. It uses navigational and hierarchical database cataloging in order to produce multidimensional inquiries. OLAP is designed to produce fast responses to these queries. Data collected in this manner is used to assess business management, sales and business process. It is also used to make predictions and forecasts for sales, budgets and investments.
Data mining is a newer computer science than OLAP. It was designed in order to process huge amounts of information about companies and other organizations. It is often used to study customer responses to advertisements, sales and promotions. Data mining is also used to build customer relationships to the company or brand. Other uses include profile building, marketing and fraud detection.