Data warehouses and their architectures vary depending upon the specifics situation. We can create with three different ways.
Basic Data Warehouse Architecture
It is a simple architecture for a data warehouse. End users directly access data derived from several source systems through the data warehouse.
he metadata and raw data of a traditional OLTP system is present, as is an additional type of data, summary data. Summaries are very valuable in data warehouses because they pre-compute long operations in advance. For example, a typical data warehouse query is to retrieve something such as August sales. A summary in an Oracle database is called a materialized view.
Data Warehouse with a Staging Area
You must clean and process your operational data before putting it into the warehouse, as shown in following Figure . You can do this programmatically, although most data warehouses use a staging area instead. A staging area simplifies building summaries and general warehouse management. Following figures illustrates this typical architecture.
Data Warehouse with a Staging Area and Data Marts
This Architecture is quite common, you may want to customize your warehouse’s architecture for different groups within your organization. You can do this by adding data marts, which are systems designed for a particular line of business.In this we illustrates an example where purchasing, sales, and inventories are separated. In this example, a financial analyst might want to analyse historical data for purchases and sales or mine historical data to make predictions about customer behaviour.