Data Warehouses and Data Marts
As organizations continue to grow in size, they are faced with the challenge of assembling data generated from various data sources for analysis and for use in the decision making process. This has given rise to the two concepts of data warehouse and data marts depending on the type of data handled by an organization at any given time. Firestone (1997), defines a data warehouse as a set of databases that have been designed by an organization to support in decision making. A data warehouse aggregates large amounts of data from various operational systems. In the contrary, a database which addresses the concerns of a particular problem in an organization is known as a data mart. A data mart contains data of relatively small amounts from specific sources such as from a single business unit. As a data warehouse holds very detailed information, a data mart holds more summarized data. Additionally, a data warehouse feeds dimensional models whereas a data mart is built using dimensional models (Moody and Kortink, 2008).
Read also Data Warehouse Origin and History
An organization can use both data warehouses and data marts to acquire data. A data warehouse is normally developed using data from various software environments. This means that a data warehouse contains different organizations resources that are needed for decision making process (Moody and Kortink, 2008). In order to acquire data from a data warehouse, an organization needs to extract the data and distribute it to different departments that find it necessary for their decision making. Data from data marts is retrieved by an organization and distributed to consumers with specific functional needs. This data is then analyzed to give information which that can be used for reporting and decision making (Firestone, 1997).
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