This syllabus is TENTATIVE – instructor reserves the right to modify the course contents and timing of activities. ISYS 650, Section 2, W 4:00 – 6:45, BUS 122, Fall, 2019 This syllabus is TENTATIVE – instructor reserves the right to modify the course contents and timing of activities. BUSINESS INTELLIGENCE Class Number #: 7665 Professor Paul Beckman, BUS 301 Office hrs: BUS 301: M: 12:00 – 2:00 Phone: 415.338.6240, [email protected] W: 12:00 – 2:00 Class of: Topic: Reading: SDT (Sharda, Delen, Turban) text Homework: Aug 28 An Overview of Business Intelligence, Analytics, and Data Science SDT Chapter 1 Sep 4 Modeling Data in the Organization; Logical Database Design and the Relational Model (neither topics is in our textbook) Sep 11 Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization; CoB Computer Lab: Begin Homework 1 SDT Chapter 2 Case write-up 1 due Sep 18 Finish Textbook Chapter 2; CoB Computer Lab: Work on Homework 1 Sep 25 Descriptive Analytics II: Business Intelligence and Data Warehousing; Work on Homework 1 SDT Chapter 3 Oct 2 Finish Chapter 3; Data Mining Example Homework 1 due; Case write-up 2 due Oct 9 Predictive Analytics I: Data Mining Process, Methods, and Algorithms; Begin Homework 2 SDT Chapter 4 Oct 16 Finish Chapter 4; Work on Homework 2 Homework 2 due Oct 23 Mid-Term Exam: Wednesday, October 23 rd Oct 30 Predictive Analytics II: Text, Web, and Social Media Analytics; Begin Homework 3 SDT Chapter 5 Case write-up 3 due Nov 6 Finish Chapter 5; Work on Homework 3 Homework 3 due Nov 13 Prescriptive Analytics: Optimization and Simulation; Begin Homework 4 ; if time: Shark Tank Network Analysis SDT Chapter 6 Nov 20 Big Data Concepts and Tools; Work on Homework 4 SDT Chapter 7 Homework 4 due Nov 27 No class: Fall Recess! Case write-up 4 due Dec 4 Finish textbook Chapter 7; Begin Homework 5 Dec 11 Future Trends, Privacy and Managerial Considerations in Analytics; Work on Homework 5 SDT Chapter 8 Homework 5 due; Case write-up 5 due Dec 18 FINAL EXAM: Wednesday, December 18th 4:00 – 5:40 FINAL EXAM!
This syllabus is TENTATIVE – instructor reserves the right to modify the course contents and timing of activities. Prerequisites: ISYS 363 (or equivalent) with grade of C- or higher. Required Texts and Materials: 1. Ramesh Sharda, Dursun Delen, Efraim Turban, Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition , Fourth Edition, Pearson Education Inc., 2018, ISBN: 978-13- 463328-2 NOTE: this textbook is available as an electronic textbook and is also for rent. Online Resources: In addition, resources from Teradata University Network () will be utilized. Please register at this web site for accessing teaching material used in class. Course Objective : This course is a study of the tools and techniques for extracting business intelligence from large volumes of data to support strategic decision making. Analysis of applications of business intelligence techniques and business analytics methodologies in different functional areas of a business will be the focus of the course. Additionally, managerial implications of business intelligence will be analyzed in this course.
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- Fall '19