Creating a Data Warehouse
Data warehouses are the latest buzz in the business world. Not only are they used to store data for reporting and forecasting, but they are part of a decision support system. There are many reasons for creating and using a data warehouse. The data warehouse will support the decisions a business needs to make, usually on a daily basis. The data warehouse collects data, consolidates the data for reporting purposes. Data warehouses are accompanied by analytical tools that accommodate forecasting as part of the decision support system. The purpose of this paper is to explore the creation of a data warehouse. Since the specifics of creating the data warehouse are determined by the database system, this paper will devote its discussion to the design or layout of the data warehouse. Before discussion of the layout of the data ware house proceeds, the basics about a data warehouse need to be discussed. Then the elements of the data ware house will be covered.
What is a Data Warehouse?
A data warehouse is a warehouse full of data, an electronic warehouse. In a manner of speaking this is true. Don Awalt describes it as follows, “A data warehouse is the cohesive data model that defines the central data repository for an organization. “ He also further stated that “we consider it a complete, integrated data model of the enterprise, regardless of how of where the data is stored.” Thus we can see that the data warehouse collects and stores the data for an organization in an organized manner that allows for analytical purposes. These purposes can be for forecasting, predictive analysis or for historical reporting. Many organizations utilize an online transaction processing system (OLTP), while the data warehouse can be used with a tool such as online analytical processing (OLAP) and data mining. Since the purpose of the OLAP differs from the OLTP, the design characteristics of a relational database that
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