Data Warehouses are a large and specialized form of a database that is used to store a company's data in a form that can be easily updated and analyzed. It contains data from transaction data, but it can include data from other sources. It separates analysis workload from transaction workload and enables an organization to consolidate data from several sources. With the advent of the data warehouse the need for heaps of physical records in innumerable filing cabinets largely ceased. No longer to modify physical paper records one by one, or to sort through masses of records to arrive at the data required. Data warehouses can perform all of the complex queries and data mining that a regular database can.
There are several characteristics of data warehousing that were created by William Inmon. These characteristics include: Subject Oriented, Nonvolatile, Integrated, and Time Variant.
Subject Oriented The way that you analyze data basing off of a subject, such as sales for a company, makes it a subject oriented data warehouse.
Nonvolatile This characteristic simply means that once data is entered, it shouldn't be changed or removed. This makes sense because this will let you analyze all collected data.
Integrated This is similar to subject oriented in the way that it handles subject material, except things such as inconsistencies and name errors must be fixed. This needs to be done so that it can be integrated correctly in the system.
Time Variant Time variant means that the data warehouse focuses on changes over time, such as from old data to new data.