This Project gives an idea of analyzing the business requirements to make a decision. The data warehousing demonstrates the principle idea to store and evaluate the data.
The Project entitled Retail business analytical processing gives the idea to demonstrate all evaluated and strategic necessities of the business requirements related to sales, stock evaluation and the systematic approach for the decision making and support.
The Project usually deals with the supermarkets, departmental store processing and the customer requirements to evaluate to develop the business by constant providing the customer requirements.
The Existing System
The current system is the database system. The usual concept of the database is to manage information in the integrated form. The data base is the record of the related information maintained in the single record or system without any error and effort for the easy accessibility of the user. The principle is to provide information in an easy, fast and less cost and effective way to the user. The database designing needs the various criteria’s.
The Proposed System
The database warehousing is simple and general in use but the application software provides the various applications.
Recording and Storing Data
The recorded data is reliable and protected as the other user cannot retrieve the data.
Reading data online and reports
The data can be observed online
Analyzing data for identifying the business trends
The application module summarizes the data and presenting various summaries for each other databases. The process is called data warehousing.
The data warehousing is important tool in the information technology. The data warehousing gives the business to make strategic decisions. The data ware housing brings out the stored data to be evaluated.
The Oracle has already implemented the data ware housing application added in the Oracle 7 version in the early 1990. The Oracle 8, Oracle 8i, Oracle 9i has the additional features of the data ware housing to enhance the performance and management of the huge data warehouses.