DESIGN & IMPLEMENTATION OF DATA WAREHOUSE PROTOTYPE WITH IN THE CONTEXT OF RELATIONAL ONLINE ANALYTICAL PROCESSING (DATA ANALYSIS)

Abstract

A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process. A data warehouse can be used to analyze a particular subject area. For example, "sales" can be a particular subject. A data warehouse integrates data from multiple data sources. For example, source A and source B may have different ways of identifying a product, but in a data warehouse, there will be only a single way of identifying a product. Historical data is kept in a data warehouse. For example, one can retrieve data from 3 months, 6 months, 12 months, or even older data from a data warehouse. This contrasts with a transactions system, where often only the most recent data is kept. For example, a transaction system may hold the most recent address of a customer, where a data warehouse can hold all addresses associated with a customer. Once data is in the data warehouse, it will not change. So, historical data in a data warehouse should never be altered. A data warehouse is a copy of transaction data specifically structured for query and analysis. This is a functional view of a data warehouse. Kimball did not address how the data warehouse is built like Inmon did, rather he focused on the functionality of a data warehouse.