UNIVERSITY OF MARY WASHINGTON -- NEW COURSE PROPOSAL Electronically submit this completed form with PDF attachments to the Chair of the College Curriculum Committee. Arts and Sciences Business Education COLLEGE (check one): X Proposal Submitted By: Gail Brooks, Chris Garcia Date Prepared: 10/23/12 Course Title: Foundations and Applications of Data Analytics Department/discipline and course number*: COB BUAD 403 *This course number must be approved by the Office of the Registrar before the proposal is submitted. Number of credits proposed: 3 Prerequisites: Grade of C or better in CPSC 220 or equivalent Will this be a new, repeatable “special topics” course? (Do you want students to be NO YES X able to take this new course more than once if the topic changes?) Date of first offering of this new course: FALL SEMESTER, year Spring 2014 Proposed frequency of offering of the course: once per year List the faculty who will likely teach the course: Chris Garcia, Gail Brooks Are ANY new resources required? NO X YES Document in attached impact statement This new course will be (check all that apply): Required in the major General Elective Elective in the major minor General Education** X **AFTER the new course is approved, a separate proposal must be sent to the General Education Committee. Catalog Description: ANLY/BUAD 403 –Foundations and Applications of Data Analytics (3). Prerequisite: CPSC 220 or equivalent. This course develops an overview of the challenges of developing and applying analytics for insight and decision-making. Examples and cases will come from customer relation management, price modeling, social media analytics, location analysis and other business domains. Cross-listed as BUAD 403. COURSE HISTORY Was this course taught previously as a topics or experimental course? Course Number and Title of Previous Course YES NO Semester Offered x Enrollment CHECK HERE if the proposed course is to be equated with the earlier topics or experimental offerings. This means that students who took the earlier “topics” course will only be able to take the new course if they made a C- grade or lower in the earlier course. NOTE: If the proposed course has not been previously offered as a topics or experimental course, explain in the attached rationale statement why the course should be adopted even though it has not been tried out. REQUIRED ATTACHMENTS: 1. Rationale Statement (Why is this course needed? What purposes will it serve?) 2. Impact Statement (Provide details about the Library, space, budget, and technology impacts created by adding this new course. Include supporting statements from the Library, IT Department, etc. as needed.) 3. Sample Syllabus Department Chair Approval: Kenneth D. Machande Date: 10/31/12 CCC Chair Approval: Gail Brooks Date: 11/7/12 UCC Chair Approval: Date: New Course Proposal Cover Sheet (July 2012) Rationale Statement This new course is intended to be part of the Data Science minor proposed. It is intended to provide students a deep familiarization with the prevalent methodologies and capabilities of the Analytics discipline. This will be accomplished by examining problems arising in various real-world contexts and solving these problems using Analytics-based approaches. This course will provide students with the “big picture” on how and when Analytics methods should be applied by exposing students to a broad range of problem domains as well as prevalent Analytics methodologies. Students will also gain experience in using Analytics approaches to solve problems through the completion of several projects. Impact Statement (Provide details about the Library, space, budget, and technology impacts created by adding this new course. Include supporting statements from the Library, IT Department, etc. as needed.) The impact of this specific course will be minimal. The plan is to have current faculty members teach the course as part of their regular teaching load. New Course Proposal Cover Sheet (July 2012) Sample Syllabus BUAD 403 Foundations and Applications of Data Analytics Prerequisite: Grade of C or better in CPSC 220 or equivalent Course Description: This course develops an overview of the challenges of developing and applying analytics for insight and decision-making. Examples and cases will come from customer relation management, price modeling, social media analytics, location analysis and other business domains. Crosslisted as BUAD 403. Learning Outcomes: 1. to comprehend the concepts and theory of data analytics 2. to analyze data from different organizational perspectives 3. to synthesize the results of the data analysis for decision making and strategic planning 4. to acquire practical experience from case studies and examples 5. to be able to decompose real-world problems and prescribe appropriate Analytics-based solution approaches Course Textbooks: Win with Advanced Business Analytics: Creating Business Value from Your Data (2013), Isson, Jean-Paul and Harriott, Jesse Harriott, John Wiley & Sons, Inc., Hoboken, NJ. How to Measure Anything: Finding the Value of Intangibles in Business (2010), Hubbard, Douglas, W., John Wiley & Sons, Inc., Hoboken, NJ. Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (2011), Williams, Graham, Springer, New York, NY. Tests/Quizzes/Final Exam: Examinations help me measure how you and the rest of the class are mastering the materials and skills of the subject. Make-up tests are not preferred and will only occur under extraordinary circumstances. If you have a conflict on a test date, please email me no later than 1 week prior to the test. The instructor will decide, based on the information provided, whether or not a make-up exam will be given. Please read the current academic catalog for final exam make-up policies. Projects and Case Studies: Two projects will be assigned to enable practical skills in the use of Analytics to be developed. Project 1 will entail predicting real estate sale prices for a set of properties using publicly available data. You will use the freely-available Rattle data mining package to complete this project. Project 2 will involve making sense of sanitized customer relations data for an office supply company. You will be required to develop a scoring model to identify the most and least profitable customers, as well as those most likely to close their accounts. You will use the freely-available Lavastorm Desktop Analytics package to complete this project. Readings and Assignments: Required class readings and assignments are essential tools for learning class material. Required class readings are due before the scheduled class meeting, except for the first class meeting of the semester. Review course material we cover in class. Assignments provide you with opportunities to practice the skills and theories introduced in the course. Several assignments will be assigned and discussed in class throughout the semester. Students are expected to complete class readings and assignments prior to the scheduled due date. A late assignment will receive a 20% deduction each day it is late. After five (5) days, a grade of zero will be given. New Course Proposal Cover Sheet (July 2012) Attendance & Participation: Class meetings include a mixture of presentation of material and interactive exercises. Attendance is required for all scheduled class meeting times and exams, and you are expected to be on time. I will randomly take attendance throughout the semester. In the rare event that an absence may occur, you are responsible for keeping up with the assigned materials and being aware of schedule or test date changes. Academic integrity It is understood that all material submitted will be pledged in accordance with the Honor Code of UMW. Disability Resources: The Office of Disability Resources has been designated by the University as the primary office to guide, counsel, and assist students with disabilities. If you receive services through the Office of Disability Resources and require accommodations for this class, please make an appointment with me as soon as possible to discuss your approved accommodations. Assessments: Exams, assignments, tests, and participation contribute to the final grade as follows Tests Final Exam Projects Total 20% 20% 60% 100% Final course grades will be assigned based on the following table. A 94% and above A- 90% to 93% B+ 87% to 89% B 84% to 86% B- 80% to 83% C+ 77% to 79% C 74% to 76% C- 70 to 73% D+ 65% to 69% D 60% to 64% F below 60% Course outline: Note: This is a tentative schedule for course readings and tests. Revisions will be announced. Assignments will be announced in class. New Course Proposal Cover Sheet (July 2012) Week 1 Readings/Assignments 2 3 4 5 6 7 Topics Introduction to course Introduction to Data Analytics Data analytics concepts Data analytics tools Data Sources Data visualization Data metrics The business value of analytics 8 9 10 11 12 13 14 15 16 Business performance measures Predictive analytics Social Media analytics Customer Relationship analytics Analytics for mobile technologies Unstructured data analytics The future of analytics Careers in data analytics Final Exam Project 1 Due New Course Proposal Cover Sheet (July 2012) Test 1 Test 2 Project 2 Due Final Exam