Data Warehousing Data Warehouse technology has changed the way that global organizations conduct business. Many have found it impossible to create a business strategy without a data warehouse. The purpose of this discussion is to research and explain the importance of data warehouse management. We will begin by defining data warehouse and describing the business uses for the technology. Our discussion will then focus of data warehouse management. We will examine the

Data Warehousing and Data Mining Executive Overview Analytics, Business Intelligence (BI) and the exponential increase of insight and decision making accuracy and quality in many enterprises today can be directly attributed to the successful implementation of Enterprise Data Warehouse (EDW) and data mining systems. The examples of how Continental Airlines (Watson, Wixom, Hoffer, 2006) and Toyota (Dyer, Nobeoka, 2000) continue to use advanced EDW and data mining systems and processes to streamline

Similarly, the Air Force needed no only some intelligent reporting capabilities, but a way that Air Force personnel, government employees, and civilian IT contractors would work together in the evaluation of applications and reports in a more robust and real-time manner. "The intent was to provide the Keystone user community the ability to do more complex financial analysis and reporting on a "self-service" basis to reduce overall system maintenance and

because the system is designed to be able to handle complex queries for information much faster than are traditional databases, designing and implementing such an attack becomes more difficult and complex (Warigon, 1997). At the same time, the ease with which information in a data warehouse can be manipulated creates more significant problems than a traditional database should unauthorized access be obtained (TechFaq, 2010). While no database or information

In addition, the support of multiple taxonomies is also critical for a data warehouse, and to the extent the architects have created a database architecture that will provide for metadata definition and re-defining of taxonomies is the extent to which the data warehouse will have greater use in the organization. Without a strong focus on these aspects of data agility, a data warehouse can quickly become outmoded and only

Since poor data quality within a system often results in poor business decisions being made from this data, it is very important that each administrator or system architect look at each customer or end-user differently, in their own unique light. Since each end-user is different, and the needs of the customer often stem from the warehouse's ability to accurately store quality information, a system that dates back to the 1970's