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Data Warehouses

As a Business Intelligence Consultant, you have been tasked with submitting a proposal for creating an enterprise data warehouse for a university.

Currently, the information is contained in a separate database by each university department (HR, Payroll, Registrar, Bursar, etc.). Some of the information contained in the various databases for students are: courses, tuition payments, extracurricular activities, scholarships, grades, and personal information. Faculty/staff: positions held, courses taught, salary & benefits, personal information, and published work or research.

They want to use this data warehouse to be able to see a single view of all university information for students, faculty, and staff. You have been tasked with creating a project plan, choosing the BI tools that will be used, and giving cost information.

1. Project Plan and Requirements for the Data Warehouse
2. Database Design
3. ETL Tool Selection
4. Data Mining/Reporting Tool

Solution Preview

1. Project Plan and Requirements for the Data Warehouse
2. Database Design
3. ETL Tool Selection
4. Data Mining/Reporting Tool20

Step 1
The first stage of the project planning is to identify and classify the users in terms of the University, students, and faulty. Also, the common problems that will be solved by the business intelligence data warehouse will be identified. The next step is to identify the information that will be expected from the data warehouse. The timeline given for the project is two months. A timeline of sixty days will be prepared for the project. The requirements of data warehouse will include assessing the university requirements. This includes the requirements of each user group including university department, students and faculty. Information has to be collected from each department/faculty. On the basis of information collected it is necessary to define dimensional model and granularity levels. The user requirement report that enables drill down, drill across, filtering and dash boarding ...

Solution Summary

The write up gives a learned discussion on Data Warehouses

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