Oakland University/Altair Engineering Technical Business Intelligence Corporate Internship Program
Guardado en:
| Publicado en: | Association for Engineering Education - Engineering Library Division Papers (Jun 26, 2011), p. 22.1113.1 |
|---|---|
| Autor principal: | |
| Otros Autores: | , , |
| Publicado: |
American Society for Engineering Education-ASEE
|
| Materias: | |
| Acceso en línea: | Citation/Abstract Full text outside of ProQuest |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Resumen: | Oakland University/Altair Engineering Technical Business Intelligence Corporate Internship Program Organizations invest significant portions of their information technology budget to capture, store,and analyze data. The return on these investments will depend on how effectively organizations analyze the data and use it to support technical product development and managerial decision making. Business intelligence (BI) or business analytics are common terms used to describe the process of building models to support decision making. This paper describes the structure and implementation of a course to give students a conceptual understanding of various modeling techniques with a focus on the application to technical decision making and solutions to business problems.The program itself is a 160-hour post-baccalaureate non-credit certificate comprised of a two-tiered course structure. Tier I of the course provides the students with a 60-hour theory overview of data mining and data-basing techniques. The application of software tools in decision making a s well as detailed case studies demonstrating how BI can be used effectively in today’s competitive product development and business environment. This includes the application of Altair Engineering Business Intelligence HiQube software using specific case studies involving applications in the product development, quality, warranty, and financial business environments.Tier II is comprised of a 100-hour, unpaid internship whereby students demonstrate their knowledge in practice at an Altair Business-host site. Students who satisfactorily complete the Tier I portion of the course proceed with the Tier II Internship. The Internship may be at a local sponsoring company within the Detroit, Michigan area, a distance company within the US, or a distance company internationally. The Internship work is project focused to assure a finite conclusion.Tier I is instructor-led since it involves skill-based software learning which necessitates a computer lab. This theory and application portion of the course meets for 10 hours per week over a six week period. Tier II may be instructor-facilitated, online, or in a web-conferencing environment. The Internship portion of the course is conducted over a 5 week period for 20 hours per week.Students and working professional that have achieved a technically-oriented Bachelor of Science or Master of Science degree are actively requited for the certificate program. Candidate students have degrees in the fields of engineering, information technology, computer science, operations management, marketing, or finance.With regard to learning objectives, students are expected to apply business intelligence/datamining analysis tools to solve real world problems through a local or distance project-oriented work environment. At the end of the course, the student should be able to: o Frame a product development or business problem to build a decision support model o Assess data needs to build a decision support model o Prepare data for mining and decision support o Build classification and clustering based decision support models o Interpret and evaluate decision support models o Understand the advantages and pitfalls of different modeling techniques.This paper will highlight experiences from the initial Certificate Program that was completed March – June 2010. Eight students with varied degree backgrounds participated in the Program.Classroom examples of data mining applied to vehicle crashworthiness star ratings and helicopter maintenance scheduling will be presented. Course outcomes will be discussed through presentation of two internship projects related to university fundraising decision making and developmental debugging of engineering simulation software. The Program assessment methods consisted of student surveys taken during both the data mining/theory and the internship course phases, and surveys completed at the companies sponsoring the student interns. |
|---|---|
| Fuente: | Library Science Database |