Instructions:
The BI solution must:
Provide real-time data access
Access historical institutional data from student databases from the past 15 years
Analytic capabilities to combine data sources (i.e., students’ data, course registrations, online/on-campus data, dates of course offerings, etc.)
Ability to predict students likely to drop out
Easy and secure access to data from multiple divisions within the university departments
BI dashboards to present and view the results
Model(s) (such as: artificial neural networks [ANN], Support Vector Machine [SVM}, and Linear Regression [LR} models) you recommend using and their rationale
You will use SAS code for the model(s) that you will use for this BI framework solution.
FOR EXAMPLE: if you’re using ANN model, write/locate ANN SAS code to include in your submission.
Explain in detail how your BI framework solution will work with the above-mentioned characteristics to help executives improve decision making. The executives are the CEO and president level as well as the vice presidents of different departments. Each department will focus on its own data while top executives will focus on the overall university total retention and costs.
Submission Requirements:
Your framework should meet the following requirements:
Three pages in length
Include the screenshot diagram(s) of the BI solution framework
Formatted according to APA guidelines as explained in the CSU-Global Guide to Writing & APA (Links to an external site.) (subheadings, one-inch margins, and double spacing)
Supported by three credible, academic outside sources in addition to course materials
Write clearly and logically, as you will be graded on content, analysis, and your adherence to the tenets of good academic writing, which should be succinct where possible while also exploring the topics appropriately. Integrate and cite scholarly sources to support your work, and supplement your ideas.
Sample Solution
