Data Warehouse Characteristics

Data Warehouse Characteristics:

Ø  Subject Oriented

Ø  Integrated

Ø  Non-Volatile

Ø  Time Variant

Subject Oriented:

                Dare warehouses are designed to analyze the data. For example, To learn more about company's Sales data, we can build a warehouse which concentrates on sales. Using this warehouse, we can answer the questions like

·         Who was our best customer ?

·         Which regions there is Max Sales ?

·         Profits and Losses wrt Previous Year Sales ?

Etc..

                This ability to define a data warehouse by subject (Sales) makes Data Warehouse Subject Oriented.

Integrated:

                Integration is slowly related to Subject oriented. Data Warehouses must put data from disparate sources into a consistent format. They must resolve such problems as naming conflicts and inconsistency among units of measure. When they achieve this, they are said to be integrated.

Non Volatile:

                Non Volatile means that once entered into the warehouse, data should not be changed. This is logical because the purpose of warehouse is to enable you to analyze what has occurred.

Time Variant:

                In Order to discover trends in business, analysis need large amounts of data. This is very much in contrast to online transaction processing system (OLTP) where performance requirements demand that historical data can be moved to an archive.

                A Data Warehouse focus on change over time is what meant by the term time variant.