ISQS 6339, Spring 2017
Data Management and Business Intelligence
Focuses: Dimensional modeling, ETL, OLAP, Data processing for analytic tasks, Introductory big data
Class meetings: TR 2:00-4:50p, BA287
Instructor: Zhangxi Lin, (806) 834-1926, Email: zhangxi.lin at ttu
Office hours: TR 10:30a-12:30p, BA E311
Social networking: LinkedIn – my TTU email, Facebook – Zhangxi.lin at gmail
(This syllabus is subject to further modification)
Data management comprises all the disciplines related to managing data as a valuable resource. Business intelligence (BI) is referred to as applications and technologies which are used to gather, provide access to, and analyze data and information about their company operations. Business intelligence systems can help companies have a more comprehensive knowledge of the factors affecting their business, such as metrics on sales, production, internal operations, and they can help companies to make better business decisions. This course is to be based on the contents covered by database management to further train students the skills methodologies, and knowledge how to accomplish data management tasks with the applications of BI tools and techniques. In this year, topics in big data, such as Hadoop/MapReduce, are added to cope with demand from the job market. The main components of this course include:
The course is lectured with cases plus in-class exercises.
Prerequisites: Database, Statistics
Assessment of Learning:
Teaching style: Case-based hands-on learning process.
Software tools to be used: Microsoft SQL Server 2016, R Services, SAS Enterprise Guide V4.2, Tableau
Print: ISBN-10 0-13-610066-X, ISBN-13 978-0-13-610066-9
eText: ISBN-10 0-13-610067-8, ISBN-13 978-0-13-610067-6
Or the older version, if available, Business Intelligence, Pearson Prentice Hall, 2008, ISBN-10: 013234761X, Turban et al
· Delivering Business Intelligence with Microsoft SQL Server 2008, by Brian Larson, Publisher: McGraw-Hill Osborne Media; November 19, 2008, ISBN 0071549447 / 9780071549448
Project and the project group:
There will be seven project teams in the class, each with no more than 5 but no less than 3 members. Project team will accomplish two data warehousing projects and present a selected big data topic in the class.
There are 12-14 exercises. Exercises could be one to two short answer questions or BI assignments to be completed in the class. All are open-book and open notes. Most of the exercises will be handed in for grading. The total credit for these exercises is 120 points. Students may be allowed to skip up to two in-class exercises without losing any credit. Missing any extra exercise will cost 10 points.
Homework is mainly the assigned readings or small projects after each class meetings, and will not be graded. These assignments will be covered in class discussions and in quizzes.
The total is 300 points
Extra bonus credit: up to 15 points based on the evaluation of the involvement in the class activities.
A – 90% or higher & overall a B or upper in exams & good attendance
B – 80-89.9% & overall a C or upper in exams
C – 70 – 79.9% & overall a C- or upper in exams
D – 60 – 69.9%
F < 60%
Requirements: Please contact me if you have any special requirements, or if I need to make special accommodations for you during the semester. I encourage you to visit with me about your progress in the course at any time.
Integrity. Academic dishonesty will not be tolerated. All students are required to adhere to the Texas Tech University Policy on Academic Honesty.
Civility in the Classroom. “Students are expected to assist in maintaining a classroom environment which is conducive to learning. In order to assure that all students have an opportunity to gain from time spent in class, unless otherwise approved by the instructor, students are prohibited from using cellular phones or beepers, eating or drinking in class, making offensive remarks, reading newspapers, sleeping or engaging in any other form of distraction. Inappropriate behavior in the classroom shall result in, minimally, a request to leave class.”
ADA Requirements. Classroom accommodations will be made for students with disabilities, if requested.
Religious Holidays. A student who intends to observe a religious holy day should make that intention known to the instructor prior to an absence. A student who is absent from classes for the observance of a religious holy day shall be allowed to take an examination or complete an assignment scheduled for that day within a reasonable time after the absence.
SAS Certificate Exams:
Selected online resources: