Data Warehouse Concepts have the following characteristics:
Subject-Oriented :
A data warehouse is subject-oriented since it provides topic-wise information rather than the overall processes of a business. Such subjects may be sales, promotion, inventory, etc. For example, if you want to analyze your company’s sales data, you need to build a data warehouse that concentrates on sales. Such a warehouse would provide valuable information like ‘who was your best customer last year?’ or ‘who is likely to be your best customer in the coming year?’
Integrated :
A data warehouse is developed by integrating data from varied sources into a consistent format. The data must be stored in the warehouse in a consistent and universally acceptable manner in terms of naming, format, and coding. This facilitates effective data analysis.
Time-variant :
Data once entered into a data warehouse must remain unchanged. All data is read-only. Previous data is not erased when current data is entered. This helps you to analyze what has happened and when.
Non-volatile :
The data stored in a data warehouse is documented with an element of time, either explicitly or implicitly. An example of time variance in Data Warehouse is exhibited in the Primary Key, which must have an element of time like the day, week, or month.