Description

A Data Warehouse is not an individual repository product. Rather, it is an overall strategy, or process, for building decision support systems and a knowledge-based applications architecture and environment that supports both everyday tactical decision making and long-term business strategizing. The Data Warehouse environment positions a business to utilize an enterprise-wide data store to link information from diverse sources and make the information accessible for a variety of user purposes, most notably, strategic analysis. Business analysts must be able to use the Warehouse for such strategic purposes as trend identification, forecasting, competitive analysis, and targeted market research.

Data Warehouses and Data Warehouse applications are designed primarily to support executives, senior managers, and business analysts in making complex business decisions. Data Warehouse applications provide the business community with access to accurate, consolidated information from various internal and external sources.

The primary objective of Data Warehousing is to bring together information from disparate sources and put the information into a format that is conducive to making business decisions. This objective necessitates a set of activities that are far more complex than just collecting data and reporting against it. Data Warehousing requires both business and technical expertise and involves the following activities:


- Accurately identifying the business information that must be contained in the Warehouse

- Identifying and prioritizing subject areas to be included in the Data Warehouse

- Managing the scope of each subject area which will be implemented into the Warehouse on an iterative basis

- Developing a scaleable architecture to serve as the Warehouse’s technical and application foundation, and identifying and selecting the hardware/software/middleware components to implement it

- Extracting, cleansing, aggregating, transforming and validating the data to ensure accuracy and consistency

- Defining the correct level of summarization to support business decision making

- Establishing a refresh program that is consistent with business needs, timing and cycles

- Providing user-friendly, powerful tools at the desktop to access the data in the Warehouse

- Educating the business community about the realm of possibilities that are available to them through Data Warehousing

- Establishing a Data Warehouse Help Desk and training users to effectively utilize the desktop tools

- Establishing processes for maintaining, enhancing, and ensuring the ongoing success and applicability of the Warehouse

Until the advent of Data Warehouses, enterprise databases were expected to serve multiple purposes, including online transaction processing, batch processing, reporting, and analytical processing. In most cases, the primary focus of computing resources was on satisfying operational needs and requirements. Information reporting and analysis needs were secondary considerations. As the use of PCs, relational databases, 4GL technology and end-user computing grew and changed the complexion of information processing, more and more business users demanded that their needs for information be addressed. Data Warehousing has evolved to meet those needs without disrupting operational processing.

In the Data Warehouse model, operational databases are not accessed directly to perform information processing. Rather, they act as the source of data for the Data Warehouse, which is the information repository and point of access for information processing. There are sound reasons for separating operational and informational databases, as described below.

- The users of informational and operational data are different. Users of informational data are generally managers and analysts; users of operational data tend to be clerical, operational and administrative staff.

- Operational data differs from informational data in context and currency. Informational data contains an historical perspective that is not generally used by operational systems.

- The technology used for operational processing frequently differs from the technology required to support informational needs.

- The processing characteristics for the operational environment and the informational environment are fundamentally different.

The Data Warehouse functions as a Decision Support System (DSS) and an Executive Information System (EIS), meaning that it supports informational and analytical needs by providing integrated and transformed enterprise-wide historical data from which to do management analysis. A variety of sophisticated tools are readily available in the marketplace to provide user-friendly access to the information stored in the Data Warehouse.