Real Time Business Intelligence at Continental Airlines Essay
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Real Time Business Intelligence at Continental Airlines
1. Describe “active” data warehousing as it is applied at Continental Airlines. Does Continental apply active or real-time warehousing differently than this concept is Normally described? Explain your answer. Answer: as shown in the case Continental senior management decided to invest in enterprise data warehouse that all employees could use for quick access to key information about the business and its customers. The data warehouse initial focus was to provide accurate integrated data revenue management. At Continental they moves real-time data, ranging from to-the-minute to hourly about customers, reservations, check-ins, operations and flits from its main operation system to Ans: As shown in the case Continental has 15 people on its data warehouse team which includes with the following designations [Data Warehouse Director]
[Data Warehouse Manager – Houston]— [Infrastructure and Application Development (2 employees)]
[Data Warehouse Manager – Miami] --- [Infrastructure and Application development (5 employees)]
[Master Data Modeler]
[User Support (4 employees)]
The first right thing the group has done is to divide their work; here each person was responsible for their work. They together manage the warehouse, develop and maintain the infrastructure, data modeling, developing and maintaining ETL processes, and also worked with the business units. These groups have been a great help for continental in implementing real-time data warehousing. On the other hand, another right thing the group has done is the communication between the employees. For example, the warehouse staff meets with the committee to inform and educate the members about warehouse-related issues. In turn, the members identify opportunities for the warehouse staff to become involved with the business areas. The warehouse teams also help to validate and write requests for additional funding. Another responsibility is to help set priorities for future directions for the warehouse
4. What elements of the data
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