Description
Business Intelligence and Analytics Spring 2016
MBAD6201-U90/DSBA 6201 – U90
Business Intelligence and Analytics
Spring 2016
INSTRUCTOR: Dr. Sungjune Park
OFFICE: 353B Friday
PHONE: (704) 687-7628
EMAIL: [email protected]
OFFICE HOURS: Mon 1:00pm-2:00pm, Wed 3:30pm – 5:30pm, and by appointment
CLASS HOURS: Wed 5:30pm-8:15pm, Friday 385
COURSE DESCRIPTION
An overview of the business approach to identifying, modeling, retrieving, sharing, and
evaluating an enterprise’s data and knowledge assets. Focuses on the understanding of
data and knowledge management, data warehousing, data mining (including rule-based
systems, decision trees, neural networks, etc.), and other business intelligence
concepts. Covers the organizational, technological and management perspectives.
Prerequisites: MBAD 5121 or equivalent.
LEARNING OBJECTIVES
Business intelligence (BI) is a broad category of applications and technologies for
gathering, storing, analyzing, and providing access to data to help enterprise users
make better business decisions. BI applications include the activities of decision support
systems, query and reporting, online analytical processing (OLAP), statistical analysis,
forecasting, and data mining. The learning objectives of the course are thus:
1. To understand the role of business intelligence and analytics in today’s
competitive and turbulent business environment.
2. To be familiar with terminology of the field, basic principles, and concepts of
business intelligence and analytics.
3. To learn how to use and apply key methods for analytics (e.g., classification,
decision trees, clustering, and association rule).
4. To use a range of tools (e.g., R, SAS Enterprise Miner, IBM SPSS Modeler)
appropriate for data analytics problems.
COURSE MATERIALS
? Handouts, slides, assignments, and online resources will be posted on Moodle.
? Textbook: There are no required textbooks as student will be provided with
enough materials for each topic on Moodle. But, recommended texts are as
follows:
o Business Intelligence: A Managerial Perspective on Analytics (3
rd
Ed.) by
Sharda, Delen, and Turban, ISBN-13: 978-0133051056
o Data Science for Business: What you need to know about data mining and
data-analytic thinking by Provost and Fawcett, ISBN-13: 978-1449361327
o An Introduction to Statistical Learning: with Applications in R by James,
Witten, Hastie, and Tibshirani, ISBN-13: 978-1461471370
GRADING
Component Points
Exams (2) 60
Assignments (5) 35
Class Participation/Attendance 5
Total 100
Final grades will be based on the following scale.
A: 90 and above, B: 80-89.9, C: 70-79.9, D: 600-699, F: 599 and below.
EXAMS
An opportunity to take an early or make-up exam is given to a student only if he/she
provides legitimate and documented reasons. Permission must be obtained from the
professor prior to the scheduled exam time. The format of make-up exams may differ
from the format of the regularly scheduled exam.
Exams are closed book and notes when they are administered in class. The instructor
will keep all exams. However, exam reviews are available during office hours or by
appointment for 10 days after exam grades are posted. All exam grades will be posted
on Moodle.
ASSIGNMENTS
Assignments will be posted at the end of the class at least a week before they are due.
Solutions must be provided via Moodle only. Detailed information on assignments’ tasks
and expected work will be given with each assignment. Assignments are due on the
given day with the start of class (5:30pm) unless stated otherwise. In case of a late
submission on the same day, 20% of the points earned from the submission will be
deducted. After the due date, the late homework may be accepted, but with a 50%
penalty. Once the grade is posted or a week has passed after due date, whichever
comes first, you will receive a 0 for the late assignment.
Each student must develop his or her own solutions to the assigned homework.
Students may not "work together" on homework assignments. Such collaboration
constitutes cheating, unless it is a group assignment. A student may not use or copy (by
any means) another's work (or portions of it) and represent it as his/her own.
ATTENDANCE POLICY
Students are expected to attend all classes. Attendance will be taken at each class and
unexcused absences will result in zero participation point. Therefore, you must inform
me ahead of time of your expected absence, tardiness, or early departure. Tardiness or
early departure is highly disruptive and is strongly discouraged in my class.
ELECTRONIC DEVICES IN CLASS
Students are permitted to use computers or tablets during class for note-taking and
other class-related work only, but this should be done without distracting other
students and without distracting you from the topic of discussion. Those using
computers during class for work not related to that class must leave the classroom for
the remainder of the class period.
However, use of cellular phones, pagers, CD players, radios, and similar devices are
prohibited in the classroom and laboratory facilities. Cellular phones MUST BE
TURNED OFF/SILENCED DURING CLASS and students are strongly discouraged
from checking their cell-phone messages when the class is in progress. Pagers must be
set to vibrate, rather than beep. Use of instant messaging, email or other
communication technologies during class time is prohibited. Calculators and computers
are prohibited during examinations and quizzes, unless specifically allowed by the
instructor.
Students violating the electronic devices policies will be marked for disruptive behavior
and may be asked to leave the class. Their grade will also be affected accordingly.
CLASS CONDUCT
Disruptive behavior in class distracts from the ability of others to profit from their in-class
experience. Such disruptive behavior includes arriving late, leaving early, cell-phone
interruptions, checking e-mail, surfing the net during the class, spending class time
working on assignments for other classes, side conversations between two or more
students during lecture, unnecessary comments that add no value to class, and any
activities that negatively impact the ability of other students to learn and/or listen in class.
Such behavior will be considered rude and inappropriate and will not be tolerated.
ACADEMIC INTEGRITY
THE UNC CHARLOTTE CODE OF STUDENT ACADEMIC INTEGRITY governs the
responsibility of students to maintain integrity in academic work, defines violations of the
standards, describes procedures for handling alleged violations of the standards, and
lists the applicable penalties. The following is a list of prohibited conduct in that Code as
violating these standards: A) Cheating; B) Fabrication and Falsification; C) Multiple
Submission; D) Plagiarism; E) Abuse of Academic Materials; and F) Complicity in
Academic Dishonesty. For more detail and clarification on these items and on academic
integrity, students are strongly advised to read the current "UNCC undergraduate and
graduate catalog."
GRADE APPEALS
If you believe that the grade you received on an assignment, exam or other graded
course component was in error or unfair, you can appeal to the professor in writing
within 10 calendar days of the receipt of your grade. The appeal should clearly state the
reasons why you believe the grade to be unfair or the nature of the error. Overdue
appeals will not be considered.
INCOMPLETE GRADE POLICY
The incomplete is not based solely on a student’s failure to complete work or as a
means of raising his/her grade by doing additional work after the grade report time. An
incomplete grade can be given when a student has a serious medical problem or other
extenuating circumstance that legitimately prevents completion of required work by the
due date. In any cases, the student's work to date should be passing, and the student
should provide proper written proof (e.g., a doctor's note), in order to get an 'I' grade.
DISABILITY ACCOMMODATIONS
If you have a disability that qualifies you for academic accommodations, please provide
a letter of accommodation from the Office of Disability Services in the beginning of the
semester. For more information regarding accommodations, please contact the Office of
Disability Services at 704-687-4355 or stop by their office in 230 Fretwell.
COURSE SCHEDULE
The Instructor reserves the right to change the course contents and/or schedule. Up-to-
date course schedule is available on Moodle. Important announcements, specific
policies regarding exams, etc. are also available on Moodle. It is the student's
responsibility to be aware of any changes in the course schedule, course contents, and
course policies by visiting Moodle regularly.
The Belk College of Business strives to create an inclusive academic climate in which the dignity
of all individuals is respected and maintained. Therefore, we celebrate diversity that includes,
but is not limited to ability/disability, age, culture, ethnicity, gender, language, race, religion,
sexual orientation, and socio-economic status.
doc_770455539.pdf
Business Intelligence and Analytics Spring 2016
MBAD6201-U90/DSBA 6201 – U90
Business Intelligence and Analytics
Spring 2016
INSTRUCTOR: Dr. Sungjune Park
OFFICE: 353B Friday
PHONE: (704) 687-7628
EMAIL: [email protected]
OFFICE HOURS: Mon 1:00pm-2:00pm, Wed 3:30pm – 5:30pm, and by appointment
CLASS HOURS: Wed 5:30pm-8:15pm, Friday 385
COURSE DESCRIPTION
An overview of the business approach to identifying, modeling, retrieving, sharing, and
evaluating an enterprise’s data and knowledge assets. Focuses on the understanding of
data and knowledge management, data warehousing, data mining (including rule-based
systems, decision trees, neural networks, etc.), and other business intelligence
concepts. Covers the organizational, technological and management perspectives.
Prerequisites: MBAD 5121 or equivalent.
LEARNING OBJECTIVES
Business intelligence (BI) is a broad category of applications and technologies for
gathering, storing, analyzing, and providing access to data to help enterprise users
make better business decisions. BI applications include the activities of decision support
systems, query and reporting, online analytical processing (OLAP), statistical analysis,
forecasting, and data mining. The learning objectives of the course are thus:
1. To understand the role of business intelligence and analytics in today’s
competitive and turbulent business environment.
2. To be familiar with terminology of the field, basic principles, and concepts of
business intelligence and analytics.
3. To learn how to use and apply key methods for analytics (e.g., classification,
decision trees, clustering, and association rule).
4. To use a range of tools (e.g., R, SAS Enterprise Miner, IBM SPSS Modeler)
appropriate for data analytics problems.
COURSE MATERIALS
? Handouts, slides, assignments, and online resources will be posted on Moodle.
? Textbook: There are no required textbooks as student will be provided with
enough materials for each topic on Moodle. But, recommended texts are as
follows:
o Business Intelligence: A Managerial Perspective on Analytics (3
rd
Ed.) by
Sharda, Delen, and Turban, ISBN-13: 978-0133051056
o Data Science for Business: What you need to know about data mining and
data-analytic thinking by Provost and Fawcett, ISBN-13: 978-1449361327
o An Introduction to Statistical Learning: with Applications in R by James,
Witten, Hastie, and Tibshirani, ISBN-13: 978-1461471370
GRADING
Component Points
Exams (2) 60
Assignments (5) 35
Class Participation/Attendance 5
Total 100
Final grades will be based on the following scale.
A: 90 and above, B: 80-89.9, C: 70-79.9, D: 600-699, F: 599 and below.
EXAMS
An opportunity to take an early or make-up exam is given to a student only if he/she
provides legitimate and documented reasons. Permission must be obtained from the
professor prior to the scheduled exam time. The format of make-up exams may differ
from the format of the regularly scheduled exam.
Exams are closed book and notes when they are administered in class. The instructor
will keep all exams. However, exam reviews are available during office hours or by
appointment for 10 days after exam grades are posted. All exam grades will be posted
on Moodle.
ASSIGNMENTS
Assignments will be posted at the end of the class at least a week before they are due.
Solutions must be provided via Moodle only. Detailed information on assignments’ tasks
and expected work will be given with each assignment. Assignments are due on the
given day with the start of class (5:30pm) unless stated otherwise. In case of a late
submission on the same day, 20% of the points earned from the submission will be
deducted. After the due date, the late homework may be accepted, but with a 50%
penalty. Once the grade is posted or a week has passed after due date, whichever
comes first, you will receive a 0 for the late assignment.
Each student must develop his or her own solutions to the assigned homework.
Students may not "work together" on homework assignments. Such collaboration
constitutes cheating, unless it is a group assignment. A student may not use or copy (by
any means) another's work (or portions of it) and represent it as his/her own.
ATTENDANCE POLICY
Students are expected to attend all classes. Attendance will be taken at each class and
unexcused absences will result in zero participation point. Therefore, you must inform
me ahead of time of your expected absence, tardiness, or early departure. Tardiness or
early departure is highly disruptive and is strongly discouraged in my class.
ELECTRONIC DEVICES IN CLASS
Students are permitted to use computers or tablets during class for note-taking and
other class-related work only, but this should be done without distracting other
students and without distracting you from the topic of discussion. Those using
computers during class for work not related to that class must leave the classroom for
the remainder of the class period.
However, use of cellular phones, pagers, CD players, radios, and similar devices are
prohibited in the classroom and laboratory facilities. Cellular phones MUST BE
TURNED OFF/SILENCED DURING CLASS and students are strongly discouraged
from checking their cell-phone messages when the class is in progress. Pagers must be
set to vibrate, rather than beep. Use of instant messaging, email or other
communication technologies during class time is prohibited. Calculators and computers
are prohibited during examinations and quizzes, unless specifically allowed by the
instructor.
Students violating the electronic devices policies will be marked for disruptive behavior
and may be asked to leave the class. Their grade will also be affected accordingly.
CLASS CONDUCT
Disruptive behavior in class distracts from the ability of others to profit from their in-class
experience. Such disruptive behavior includes arriving late, leaving early, cell-phone
interruptions, checking e-mail, surfing the net during the class, spending class time
working on assignments for other classes, side conversations between two or more
students during lecture, unnecessary comments that add no value to class, and any
activities that negatively impact the ability of other students to learn and/or listen in class.
Such behavior will be considered rude and inappropriate and will not be tolerated.
ACADEMIC INTEGRITY
THE UNC CHARLOTTE CODE OF STUDENT ACADEMIC INTEGRITY governs the
responsibility of students to maintain integrity in academic work, defines violations of the
standards, describes procedures for handling alleged violations of the standards, and
lists the applicable penalties. The following is a list of prohibited conduct in that Code as
violating these standards: A) Cheating; B) Fabrication and Falsification; C) Multiple
Submission; D) Plagiarism; E) Abuse of Academic Materials; and F) Complicity in
Academic Dishonesty. For more detail and clarification on these items and on academic
integrity, students are strongly advised to read the current "UNCC undergraduate and
graduate catalog."
GRADE APPEALS
If you believe that the grade you received on an assignment, exam or other graded
course component was in error or unfair, you can appeal to the professor in writing
within 10 calendar days of the receipt of your grade. The appeal should clearly state the
reasons why you believe the grade to be unfair or the nature of the error. Overdue
appeals will not be considered.
INCOMPLETE GRADE POLICY
The incomplete is not based solely on a student’s failure to complete work or as a
means of raising his/her grade by doing additional work after the grade report time. An
incomplete grade can be given when a student has a serious medical problem or other
extenuating circumstance that legitimately prevents completion of required work by the
due date. In any cases, the student's work to date should be passing, and the student
should provide proper written proof (e.g., a doctor's note), in order to get an 'I' grade.
DISABILITY ACCOMMODATIONS
If you have a disability that qualifies you for academic accommodations, please provide
a letter of accommodation from the Office of Disability Services in the beginning of the
semester. For more information regarding accommodations, please contact the Office of
Disability Services at 704-687-4355 or stop by their office in 230 Fretwell.
COURSE SCHEDULE
The Instructor reserves the right to change the course contents and/or schedule. Up-to-
date course schedule is available on Moodle. Important announcements, specific
policies regarding exams, etc. are also available on Moodle. It is the student's
responsibility to be aware of any changes in the course schedule, course contents, and
course policies by visiting Moodle regularly.
The Belk College of Business strives to create an inclusive academic climate in which the dignity
of all individuals is respected and maintained. Therefore, we celebrate diversity that includes,
but is not limited to ability/disability, age, culture, ethnicity, gender, language, race, religion,
sexual orientation, and socio-economic status.
doc_770455539.pdf