Business Intelligence Files
Shyam Varan Nath
This presentation will look at the framework for developing a data-driven planning application using business intelligence and advanced analytics. Often the planning, budgeting, and forecasting involves quantitative details that make the job of the approving authorities harder. Here we take the domain of K-12 education and look at how advanced analytics can be used to predict the students who are "at-risk" of graduation versus those who are likely to succeed. This is a major U.S. national challenge and the government's "No-Child Left Behind" initiative addresses that. We look at how K-12 cross-subject education related data such as attendance, enrollment, achievement, discipline, etc. can be used to create an education datawarehouse and can be used for data mining. We will look at the use of Oracle Warehouse Builder, Oracle Data Mining, OBIEE, other BI tools, and the development environment in the process. The outcome of the data mining provides the "actionable" data to the education administrators and decision-makers via the education dashboards. These in turn help to initiate data-driven planning that can use the results of predictive analytics to plan for current and future school years. This presentation was developed using a real Department of Education BI project from 2007.