University of Dayton
School of Business Administration
Spring, 2017

MIS 366/MBA 667A
Business Intelligence

DFINAL VERSION - PENDING ANY UNFORESEEN CHANGES.

Any substantive changes to this document will appear with Light Blue Highlight.

Something interesting to read about grades. 

Get your grades (on Isidore), and teams (coming soon). 
Jump to course schedule

Tableau's data visualization software is provided through the Tableau for Teaching program.  Thanks Tableau!

This page was last modified on Monday May 01, 2017

INSTRUCTOR:
OFFICE:
PHONE:
EMAIL:

WEB PAGES:

CLASS MEETINGS:
OFFICE HOURS:
Dr. David Salisbury
Anderson Center, Room 103
937.229.5085 (office); 937.229.1030 (facsimile)
salisbury@udayton.edu
http://www.davesalisbury.com/ (professor)
http://www.davesalisbury.com/classtuf/mis366_mba667a/ (course)
T/R @ 1100 AM-1215 PM in MH 102
M 11-1, T/R 2-3, W 1230-230 (email usage is encouraged) or by appointment.  Hours subject to change due to unforeseen circumstances.  Any changes will be communicated to students via email.

Course Overview

This course will provide students with a comprehensive understanding of the conceptual overview of the field of Business Intelligence (BI).  The class is not intended to be highly technical, nor will it require significant statistical knowledge (beyond that you should have already had).  This said, technology and analytics will be reviewed as part of the course.  Rather, this is a course about developing a capacity for BI in your current or future organizations.  We will cover frameworks, concepts, methods, skills and technologies necessary to make effective decisions rapidly.  Consistent with the over-arching theme of the IS discipline, we will investigate information - how to capture and store it, how to deliver it to decision-makers and how to create systems that decision-makers can use to find answer they need to do their jobs effectively.  As such, we will learn about topics such as data quality, data warehousing, data mining, business performance management, multi-dimensional data analysis, on-line analytical processing, visualization and others.  We will also address factors that lead to BI success and applications/impacts of BI in organizations.

As with all courses in the School of Business Administration at the University of Dayton, this course attempts to advance the University and School mission, to wit:

The School of Business Administration is a learning community committed in the Marianist tradition to educating the whole person and to connecting learning and scholarship with leadership and service in an innovative business curriculum designed to prepare students for successful careers in the contemporary business environment. 

To this end, the BI course is designed to bring theory about BI design and use into the course, allow you to put this learning into practice building a prototype BI system, and by doing so contribute to your understanding of how information systems are designed and built so you may eventually apply this knowledge in your future careers. 

Course Texts

Some of you may choose to get the books at the UD bookstore.  However, it is anticipated that some will engage in whatever searches are necessary to secure the appropriate books at the lowest cost.  Hence, ISBN's are provided so you may verify that the book you get is the one I'm using.  I am not responsible for books that do not match.  The total book cost should be around $90 if you go to Amazon and buy new; book store will be slightly higher.  Your mileage will vary. 

Sharda, R., Delen, D., and Turban, E. (2014).  Business Intelligence: A Managerial Perspective on Analytics (3rd Edition).  Upper Saddle River, NJ: Pearson.  ISBN: 978-0-13-305112-4.

Davenport, T. H., Harris, J. G. and Morison, R. (2010).  Analytics at Work: Smarter Decisions, Better Results.  Cambridge, MA: Harvard.  ISBN: 978-1422177693.  A bit updated over the 2007 book, with a bit more direct managerial advice rather than bigger picture stuff.

A functional laptop computer with appropriate software.

Readings available at the MIS BI Course Site (on Isidore).  Other materials to be distributed as necessary, either electronically or in class. 

I'd also recommend the following for reading (but do not require you to purchase):

Davenport, T. H. and Harris, J. G. (2007).  Competing on Analytics: The New Science of Winning.  Cambridge, MA: Harvard. ISBN: 978-1-4221-0332-6. This book is still pretty good, and can be found cheaply at places like Alibris.

Davenport, T. H. (2014).  Big Data at Work:  Dispelling the Myths, Uncovering the Opportunities.  Cambridge, MA: Harvard Business School Press.  ISBN: 978-1422168165.

Eckerson, W. W. (2011).  Performance Dashboards: Measuring, Monitoring and Managing Your Business (2nd Edition).  Hoboken, NJ: John Wiley.  ISBN: 978-0-471-72417-9.  His 2006 book was really good; this one updates it with new cases and insights derived since then.   

Hubbard, D. W. (2007).  How to Measure Anything:  Finding the Value of Intangibles in Business.  Hoboken, NJ: John Wiley (website: http://www.howtomeasureanything.com). ISBN: 978-0-470-1102-6.  Pretty good for discussions of how to identify meaningful surrogates for things you need to measure.

Vitt, E. Lukevich, M., and Misner, S. (2002).  Business Intelligence: Making Better Decisions Faster.  Redmond, WA: Microsoft Press.  ISBN: 978-0-7356-26660-7 .  Pretty decent read, and the cases in it aren't bad either.

Fishman, C.  (2006).  The Wal-Mart Effect:  How the World's Most Powerful Company Really Works - and How It's Transforming the American Economy.  New York: Penguin.  ISBN: 978-0-1430-3878-8.  Puts Wal-Mart in context.  Not an anti Wal-Mart screed, but does raise worthwhile issues, and along the way describes in limited detail some aspects of its BI efforts.

Course Procedures

Overview

The course deals primarily with BI concepts, and the design and implementation of such systems.   

Practical Experience

An important aspect of the course will be the emphasis on understanding how BI systems are developed and built through the development of such systems using various tools and techniques of the profession.  Some assignments will be performed individuals (to help each of you build your own skills), and others as teams (reflecting that much system development happens in teams).  You will also be required from time to time to assess/summarize readings throughout the semester. 

Course Assignments

A large proportion of each student's grade in this course will be assessed on the basis of the student's performance on various assignments that are expected to be completed through the semester. All assignments are to be completed by individuals, unless otherwise stated on the assignment. All assignments for this course are to be made via the World Wide Web, at the URL noted above. 

Timeliness of Assignment Submission

It is important to submit assignments on time. All assignments are due on the assigned date. Late assignments will not be accepted. You are all going to be in the real world someday, and this is how they do it there. This policy will be strictly enforced, except as mentioned under the excuses section. Please also know that if the first assignment is late, you put yourself severely behind for subsequent assignments.

Please be aware that no excuses except the approved ones noted in this document below will be accepted for assignments not being submitted on time, unless it's really good.

You should also be aware that you are responsible to see that your assignment has been submitted properly. I am not going to be chasing people down to make certain that they have submitted their work. In addition, due to the number of assignments in a class like this, you are also responsible to keep backups of all submitted work in case something gets lost in the shuffle, and you should keep all returned assignments until the end of the semester as proof they were submitted and marked.  Finally, marks which have been posted for one week are final.  Hence, you should keep track regularly of your course marks as posted on the database. 

Finally, to discourage procrastination, I will offer no assistance on class assignments after 5PM on the day before they are due. This policy will be strictly enforced.  If an assignment is due on Wednesday (as an example), the last assistance I will render ends at 5PM on Tuesday. 

Class Attendance and Participation

Class time will be devoted to lectures, case discussion, demonstrations of database topics, and open discussion concerning database development issues. Contrary to popular belief, my job is not merely to impart information to you, but to help you learn. The mind is not a vessel to be filled, but a fire to be lighted. Your participation is extremely important to the learning process for yourself and the entire class. Consequently, class attendance and participation are strongly encouraged. For your information, I do keep a participation record, and it will influence your mark. Please also note that attendance is not the same as participation.   Finally, please be advised that after three misses (non-excused per policy below) the participation mark will be reduced to zero.

Another encouragement to attend is that you are responsible for anything that transpires in class. If you miss an assignment due date or other changes because you were not in class (or don't get it via email), it is your problem.

Classroom Decorum

You should be aware that your actions in the classroom environment should demonstrate intellectual engagement in the course content, and as well respect for your classmates and for your instructor. As such, talking audibly, passing notes, and other similar juvenile behavior simply have no place in a university classroom. If you find yourself unable to avoid chatting with the person next to you, you should consider sitting elsewhere in the class. Expect to be called out when such behavior is observed.

Other behaviors that are disruptive to others' learning involve various electronic devices. Cell phones, pagers and similar electronic communication devices should be turned off and stowed below the desk in a case or bag during all classes. While these devices are useful in their appropriate context, they create a disruption to the learning environment when they go off in class. Further, leaving the room to take a cell phone call is both inappropriate and rude, and also causes a disruption to the learning environment. As a consequence, failure to comply with this policy will result in appropriate disciplinary action, up to and including referral to university judiciaries.

Relevant to computer use (either in laptop required sections or in the lab), engaging in IM sessions, web-browsing, reading your email and other behavior of this type means that you are not paying attention to the material being discussed. Almost invariably this results in disruption to the learning environment as students who have not been paying attention find themselves behind and ask questions that have already been addressed. When you are in the classroom, you are expected to be engaged intellectually.

The instructor reserves the right to limit or prohibit use of any programmable devices (e.g. programmable calculators, laptop computers) and devices for communication and data storage (including but not limited to camera phones, cell phones, pagers, storage media or PDAs) at any time in the classroom. Refusal to comply with a request of this nature will result in sanctions being assessed as appropriate, up to and including referral to university judiciaries.

Please do not leave the class once you have chosen to attend -- it tends to be distracting for the rest of the class. If you must leave early, please sit near the door to make your departure unobtrusive, or do not attend at all. Please do not be late when you attend. Too many people coming after class starts creates a real disturbance. I reserve the right to take corrective action if it becomes a problem.

You should also be aware that being late for classes is no excuse to receive extra time on in-class activities or assignment submission deadlines. To arrive late disrupts the learning environment and, unless there is ample reason (see approved reasons, below) also demonstrates lack of respect for your classmates.  If you are late for class on a day with a required in-class activity you will have less time to complete this. Finally, when assignments are due at the start of class, arriving late to class (i.e. significantly after the assignment has been taken up) is grounds for the assignment due that day to be considered a late submission.

I reserve the right to take corrective action if these issues create problems.

Please know that the intent of these policies is not to be unreasonable; from time to time a student may have reasonable need to leave the classroom prior to the end of class, or may have a legitimate reason that they are late. For example, he/she may be ill, may need a drink of water, may need to avail him/herself of the restroom facilities, or in winter for those driving weather can be a challenge. Further, there are emergency situations in which constant availability via electronic communication may be necessary. In this case, simply notify the instructor of the situation and a reasonable accommodation can be made.

Reading Assignments

While there is not a large amount of material to be covered through this course, it is rather easy to fall behind. Please ensure that you stay current in your readings -- it is expected that you will have read in advance the material to be covered in class on a given day, and be able to discuss it.

Communication with the instructor

While I am around a lot, I am not in perpetually. Consequently, much interaction with me will be through e-mail (salisbury@udayton.edu).  You should also note that I intend to communicate with you via email as well; hence, it is important that you check your email often. 

Examination Procedures

The examinations will contain case-based questions, objective-style questions, and problem-solving questions. Exams will be based on the required text, on the in-class material associated with computer software, and on the other readings assigned by the instructor. Please note this carefully: There will be NO make-up examinations, save for university-approved reasons. If you must miss an examination, be prepared to document a university-approved reason. Job interviews, site visits and incarceration due to over-exuberant St. Patrick's Day participation are examples of reasons that are NOT university-approved.

Grading Scale and Course Components

The grading scale and grading components are presented below. If you make any of the cut-offs, you will receive that mark. For example, if you earn 930 points, you will receive an "A" for the course, or if you receive 885 points, you will receive a "B+" for the course.

MIS 366 Grading Scale

Grade Assignment

Grade Components

(A)
(A-)
(B+)
(B)
(B-)
(C+)
(C)
(C-)
(D)
(F)

>=930
>=900 <930
>=870 <900
>=830 <870
>=800 <830
>=770 <800
>=730 <770
>=700 <730
>=600 <700
<600 (failure)

Individual Homework
Team Project
Class Participation
Lowest Exam Score
Highest Exam Score

Total Points

350
150
75
200
225

1000

MBA 667A Grading Scale

Grade Assignment

Grade Components

(A)
(A-)
(B+)
(B)
(B-)
(C)
(F)

>=930
>=900 <930
>=870 <900
>=830 <870
>=800 <830
>=700 <800
<700 (failure)

Individual Homework
Main Team Project
Case Write-Up/Presentation
Class Participation
Lowest Exam Score
Highest Exam Score

Total Points

300
150
100
75
175
2
25

1000

Since the marks in my classes over the long term tend to look like a normal curve, I tend not to force an artificial curve. On the odd chance that there is a curve it will be applied only on the overall grade in all sections I teach. Thus, no question of curving will be entertained until after the final. In addition, no extra credit assignments will be offered; if you are unable to perform well on what has already been assigned, I donít wish to burden you with extra work.  Finally, I encourage you that if you are in trouble, try to demonstrate an effort to improve and ask for help. Do not fail in silence.

Academic Dishonesty

I will vigorously pursue the prosecution of academic dishonesty. It is understood and that students often learn and work together; consequently you may be asking questions or getting help from others. Be very clear, however, that there is a reasonably obvious distinction between "help" and "cheating", which I will elaborate often in class throughout the semester. In instances where such misconduct is proven, I will invoke University of Dayton policy to the fullest extent. Please consult the most recent edition of the "Student Handbook" for further information on Student Code of Conduct and Academic Policies.

You should also note that the way individuals carry out their roles as a members of a project team could jeopardize the other members of the team with respect to academic misconduct. Specifically, if a team member fails to participate in the manner called for, and appends his/her name to the team's final product, each member of the team is deemed to have been academically dishonest. Thus, it is in each team member's interests to make certain that all team members participate appropriately, and to bring any occurrences of inadequate participation on the part of other members to my attention. Please be aware that the team defines adequate participation; it is reasonable to assume that on a given portion of the assignment some members will contribute more than others. However, this should balance out, and on the bulk of any given assignment, the level of participation should be equitable for all so that all team members receive a good educational experience.

Intellectual Property Rights

The advent of websites such as Course Hero forces your instructor to issue a reminder regarding the intellectual property rights of various persons or organizations, including but not limited to your instructor, any guest speakers and course text author's rights. You should be aware that 
ALL assignments, examinations, worksheets, problems, projects, documents, recordings, or other materials distributed or used in this course cannot be reproduced, distributed, or transmitted in any form or by any means, including but not limited to scanning, photographing, copying, uploading, or other electronic methods, without the prior written permission of the instructor or copyright holder.  Any violation of this notice may result in a charge of academic dishonesty, academic penalties, other University disciplinary action, and/or legal recourse.

Acceptable Excuses for Rescheduling Exams, Late Assignments, etc.

Note: It is conceivable there are other acceptable excuses that I've not anticipated, but you must receive permission from me personally in advance.

Additional Learning Support for Students

The University of Dayton and your instructor are committed to providing equal access to its educational opportunities for all our students, including those in need of accommodation due to disability.  Students who believe they have such need are invited to meet with your instructor privately to discuss specifics.  Formal disability-related accommodations are determined by the Office of Student Learning Support using specific guidelines.  As a consequence, it is important that a student needing accommodation be registered with SLS and notify your instructor of your eligibility for such accommodation with a signed SLS Self-Identification Form.  With this, and in consultation with the SLS, your instructor will devise the appropriate accommodation(s) for your need.

Even if you do not have special needs per se, you may find resources provided by the Office of Student Learning Support helpful, with a variety of services to assist you in achieving academic success at the university, including study skills classes and workshops, tutoring and consultations, et cetera. 

Four Easy Ways to Raise Your Grade

Changes to the Syllabus

Since the main objective of this class is for you to learn relevant and useful stuff. I reserve the right to alter the syllabus as necessary to meet this goal. Any such changes will be announced, in class, and will be explained.

Finally

I took this position because I enjoy teaching. I genuinely care about you and your progress in the class. If you have a problem, complaint, comment, concern, etc., please schedule an appointment or drop in during open office hours.

Schedule--Subject to review and change.
Assignment links will be added soon.
 

Month Date

Anticipated Topics

Class Slides, Reading Chapter Assignments
and/or Due Dates
(% is of Assignment Total)
Assignments are found in Isidore in Assignments Folder
Slides will be in Isidore in the Slides Folder.  These will be posted before a given topic is covered in class.
January T 17 Course introduction, overview of BI Sharda/Delen/Turban (SDT) 1
R 19 Course introduction continues Davenport, Harris, Morison (DHM) 1 (and "Part 1")
T 24    
R 26 Teradata University Network Introduction Assignment 1 DUE Nationwide (10%) INDIVIDUAL
Tour of the Teradata University Network Site - Student Password "Analytics"
T 31 Data Warehousing SDT 2
February R 2 Data DHM 2
Assignment 2 DUE Teradata (5%) INDIVIDUAL
T 7 Business Reporting, Visual Analytics, BPM SDT 3
R 9  SAS Visual Analytics Introduction
Continue Reporting, Visual Analytics, BPM
T 14 Continue Reporting, Visual Analytics, BPM  
R 16 Enterprise DHM 3
Assignment 3 DUE SAS Visual Analytics (15%) INDIVIDUAL
T 21 Leadership and Targets DHM 4,5
R 23 Analysts DHM 6
T 28 Guest Speaker - Jake Temme Assignment 4 DUE SAS Visual Analytics (15%) INDIVIDUAL (NOW DUE WEDNESDAY, MARCH 1 by 5PM)
March R 2 Spring Break - No Class  
T 7 Review and Catch-Up, Discuss Project Proposals Team Project Proposals Due (details in Isidore)
R 9 MIDTERM EXAMINATION covers all content covered in class by 28 Feb.
T 14 Tableau Introduction
Assignment 5 DUE SAS Visual Analytics (10%) INDIVIDUAL
R 16 Data Mining SDT 4
T 21 Data Mining & Embedding Analytics SDT 4
DHM 7 (and "Part 2")
 
R 23 Text and Web Analytics SDT 5
Assignment 6
DUE Tableau (10%) INDIVIDUAL
There's a Tableau practice assignment (old Assignment 6) available in Isidore also. 
T 28 Text and Web Analytics
Building an Analytical Culture
SDT 5
DHM 8
R 30 Big Data SDT 6
Assignment 7 DUE DATAMINING TD (10%) TEAM
April T 4 Big Data continues
Reviewing the Business, Meeting Challenges
SDT 6
DHM 9, 10
R 6 Guest Speaker - Ryan Cronin Assignment 8 DUE  SQL IN TD (15%) TEAM
T 11 Emerging Trends and Stuff, Cybersecurity Analytics SDT 7 - relevant articles will be sent before 4/11.
R 13 Easter Break - No Class  
T 18 STUDENT EVALUATION OF TEACHING FIRST 15 MINUTES.
Toward More Analytical Decisions
DHM 11
R 20 Independent Team Project Work Day Assignment 9 DUE  SENTIMENT (10%) INDIVIDUAL
T 25 MBA Presentation, Team project presentations MBA Project DUE
Final Team Project Deliverables DUE 
R 27 Team project presentations Final Team Project Deliverables DUE
May M 4 FINAL EXAMINATION, Thursday May 4, 2017, 12:20-2:10 PM (from UD Examination Schedule)

ALL assignments are due at (or before) the START of class.