School of Information Systems

The Characteristics of The Data Warehouse

07 Mar 2024

There are four characteristics of a data warehouse. The following describes all its characteristics: 

1. Subject Oriented 

Data Warehouse has a subject oriented nature because it is designed to analyze data based on certain subjects (depending on the person) who are in a company and the need for the Data Warehouse to store data that supports decisions so that it is not on the process or application functions that are data oriented. Data Warehouse is organized by the main subjects related to the company such as customers, products, and sales so it is not organized in the main applications such as customer invoicing, stock control, and product sales. 

2. Integrated 

Data Warehouse has the ability to store data originating from separate sources into a consistent and integrated format with each other so that data cannot be broken down because the data has become a single entity that supports the whole concept of Data Warehouse itself. The requirements for data source integration are met in a consistent manner in variable naming, variable size, coding structure and physical attributes of the data. This is because it is possible that in the application there are variables with the same intent but different formats so that these variables need to be converted to an agreed format and the data can be said to be integrated data. 

 3. Time Variant 

Data Warehouse stores data that has a time dimension that may be used as business records for any given time (Data Warehouse stores historical data) so that all data in the Data Warehouse can be called accurate or valid only at certain times. In the Data Warehouse, it often stores various kinds of time such as when a transaction occurs/changed/cancelled, when it enters the computer, and when it enters the Data Warehouse. And the version is also always stored as when a postal code definition changes, the old and new data are in the Data Warehouse. Also, the time variance is also expressed in terms of data retention time, implicit or explicit time associations with all data, and presented data representing a series of snapshots. 

4. Non-Volatile 

Data Warehouse cannot be updated continuously (real time) but by refreshing the operating system periodically so that it can be said that the new data added is used as a complement to the database itself and not for changes. This is because the database absorbs new and incremental data with the previous data. Data in the Warehouse is also periodically uploaded within the same time frame (e.g., every morning or every weekend). The data warehouse only has 2 data manipulation events, namely loading data and accessing data, it is not possible/difficult to update but can only add new data. 

References: 

 

Lily Janvieka