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MIS2502.011 – Data Analytics
Summer 2015
About the Instructor:
Jeremy Shafer (jeremy@temple.edu)
209D Speakman Hall
Phone: (215) 204-6432
Profile: http://community.mis.temple.edu/jshafer
Office hours: 10:00-11:00, Tuesdays and Thursdays, Main Campus. (I can be available via WebEx at other
times if you schedule with me accordingly.)
Class Location and Time:
Alter Hall 232
1:30pm – 4:25pm on Monday, Wednesday
On the web:
http://community.mis.temple.edu/mis2502001summer2015
Course Description:
The course provides a foundation for designing database systems and analyzing business data to enhance firm
competitiveness. Concepts introduced in this course aim to develop an understanding of the different types of
business data, various analytical approaches, and application of these approaches to solve business problems.
Students will have hands-on experience with current, cutting-edge tools such as MySQL and SAS.
Course Objectives:
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•
•
•
•
•
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Articulate the key components of an organization’s information infrastructure.
Create data models based on business rules.
Create a transactional database from a model using SQL.
Create an analytical data store by extracting relevant data from a transactional database.
Perform extract, transform, load (ETL) functions such as data sourcing, pre-processing, and cleansing.
Discover trends in analytical data stores using the data mining techniques of clustering, segmentation,
association, and decision trees.
Present data visually for clear communication to a managerial audience.
Required Textbook:
There is no required textbook for this course.
MIS2502
Syllabus
Evaluation and Grading:
Item
Exams (2)
Assignments (pass /
fail)
Participation
Percentage
80%
10%
10%
94 – 100
90 – 93
87 – 89
83 – 86
80 – 82
77 – 79
Page 2
A
AB+
B
BC+
Scale
73 – 76
70 – 72
67 – 69
63 – 66
60 – 62
Below 60
C
CD+
D
DF
Once a grade is communicated to you electronically you will have a 1-week window in which to approach me
and question the grade you received. I won’t consider grade adjustments of any sort after that 1-week
window.
Exams:
There will be two exams during the semester. The date of the first exam is 6/1/2015 and the date of the
second exam is 6/17/2015.
Make-up exams will not be given under most circumstances. Exceptions are granted at my discretion and are
typically limited to extreme circumstances such as documented hospitalization or funeral attendance. If you
are permitted, by me, to take a make-up exam or quiz, I reserve the right to substitute an alternate exam with
different content. Students may find the content of the make-up exam or quiz to be more difficult than the
original. It is, therefore, to your advantage to show up for the exam or quiz at the scheduled time and take it
with the rest of the class.
Assignments:
There will be five assignments.
#
1
2
3
4
5
Topic
SQL #1 – Getting Data out of the Database
SQL #2 – Putting Data into the Database
SAS #1 – Decision Trees
SAS #2 – Clustering
SAS #3 – Association Rules
Due Date
FRIDAY 5/22
MONDAY 5/25
FRIDAY 6/5
FRIDAY 6/12
MONDAY 6/15
These assignments will be awarded a pass / fail grade. A “pass” is worth 2 points, a fail is worth 0 points, and
an assignment turned in past its due date will be awarded no more than 1 point. Assignments are considered
late if they are turned in after 11:59 pm the day on which they are due.
Spring 2015
Jeremy Shafer
MIS2502
Participation:
Syllabus
Page 3
Participation counts for a portion of your class grade. Your participation grade is assigned at the discretion of
your instructor. You participation grade will be assigned at the end of the semester. Here is a short list of
things I will consider when assigning your participation grade:
• Did you complete the in-class exercises and respond to the weekly questions? Note that these
indicators are my most concrete measure of class participation. I will ask you to upload your in class
work to your owlbox folder, and I expect you to respond to the question of the week on the class
blog.
• Did you attend class regularly?
• Did you thoughtfully contribute to course related conversations in class and online?
• Did you work independently? Or did you rely too heavily on assistance from others?
• Did you manage your time responsibly and consider scheduled quiz and exam dates in your decisionmaking?
• Did your conduct distract other students and/or impede their learning?
Submitting your work
On the first day of class I will require each student to set up a folder on owlbox (see: owlbox.temple.edu) and
share it with me.
I expect you to submit your work to me by copying files into that folder. I will use the time / date stamp on
the files to determine if they are on time or late. I expect you to submit both your in-class exercises and
assignments to me in this fashion.
Extra Credit and “Grading on the Curve”:
I generally do not give extra credit opportunities. In the unlikely event that I do offer an extra credit
opportunity, I will make it available to the whole class. I will not offer individuals extra credit opportunities as
a way to compensate for poor academic performance earlier in the semester.
I generally do not curve grades and have no plans to do so this semester. If I decide that a curve is necessary,
it will be applied at the end of the semester.
Classroom Etiquette:
The environment you and your fellow students create in class directly impacts the value gained from the
course. To that end, the following are my expectations regarding your conduct in this class:
• Arrive on time and stay until the end of class.
• Turn off cell phones, pagers and alarms while in class.
• Limit the use of electronic devices (e.g., laptop, tablet computer) to class-related usage.
• Be fully present and remain present for the entirety of each class meeting.
• Do not engage in side discussions while others (including me) are speaking.
Spring 2015
Jeremy Shafer
MIS2502
Syllabus
Page 4
Attendance:
If you miss all or part of class it is your responsibility to catch up, talk to your fellow classmates; check the class
blog, complete readings, etc. While every student is encouraged to visit with me during office hours to help
them gain a better understanding of material which they didn’t fully understand when they were in class,
office hours are NOT for helping students catch up on material they missed because they were absent.
Plagiarism and Academic Dishonesty:
Please see the following:
http://bulletin.temple.edu/undergraduate/about-temple-university/student-responsibilities/
It is important to do your own work, and to not present the work of others as if it were your own. Cheating
and plagiarism will not be tolerated in this class. Penalties for such actions are given at my discretion, and can
range from a failing grade for the individual exam or quiz, to a failing grade for the entire course, or to
expulsion from the program.
Student and Faculty Academic Rights and Responsibilities:
The University has adopted a policy on Student and Faculty Academic Rights and Responsibilities (Policy #
03.70.02) which can be accessed through the following link:
http://policies.temple.edu/getdoc.asp?policy_no=03.70.02
MIS Department Portfolio Requirement:
The MIS department has instituted a portfolio requirement for MIS majors. Here are two excellent resources
that describe why the MIS portfolio points are important to you.
1. http://community.mis.temple.edu/current-students/professionalachievement
2. http://community.mis.temple.edu/store
You are STRONGLY encouraged to, at a minimum, do the following to earn portfolio points:
1. Create an e-Portfolio and have it listed with the department.
2. Become an active member of AIS and participate in professional development activities.
3. Attend the IT Awards Reception (spring semester only) and the MIS Department’s Career Fair.
4. Volunteer your time for department-sponsored events.
5. Discuss opportunities to earn points for projects with your MIS instructors.
Spring 2015
Jeremy Shafer
MIS2502
Syllabus
Page 5
Schedule:
Keep in mind that all dates are tentative – check the Community site regularly for changes in the schedule.
Date
Week Day
Topics
5/11/15
1
1
Course Introduction and Syllabus
1
1
The Information Architecture of an Organization
1
1
1
2
Data Modeling; Gathering requirements;
Introducing The Entity-Relationship Diagram
More on ERDs: Relationships, cardinality
1
2
1
2
2
3
2
3
2
3
2
3
2
4
Creating and updating the database; SQL CREATE,
DROP, and ALTER; SQL INSERT, UPDATE, and DELETE
2
4
In-class exercise: Working with SQL, part 2
5/25/15
3
5
MEMORIAL DAY – NO CLASS
PowerPoint: ETL
(RECORDED LECTURE)
5/27/15
3
6
Turning transaction data into analytical data: Overview
of the Dimensional Model
PowerPoint: Dimensional
Data Modeling
3
6
3
6
The structure of the Dimensional Model: The Star
Schema
In-class exercise: Pivot Tables in Excel
4
7
EXAM 1
4
7
Introduction to Advanced Analytics and SAS Enterprise
Miner
4
7
In-class exercise: Introduction to SAS Enterprise
Miner/Preparing Data for Analysis
*
5/13/15
5/18/15
5/20/15
**
6/1/15
Spring 2015
In-class exercise: Creating an entity relationship
diagram
From ERDs to Schemas: Normalization, primary/foreign
keys, joins
In-class exercise: Converting ERDs to schemas
Getting data out of the database: SQL SELECT, DISTINCT
MIN, MAX, COUNT, and WHERE; Make sure you’ve
done the MySQL tutorial and reviewed the MySQL
PowerPoint deck.
In-class exercise: Pen-and-paper SQL exercise
Course Materials
PowerPoint: Information
Architecture
PowerPoint: Relational
Data Modeling
PowerPoint: Relational
Data Modeling
PowerPoint: Relational
Data Modeling
PowerPoint: SQL 1
Getting data out of the database: Joining tables, SQL
subselects, LIMIT
In-class exercise: Working with SQL, part 1
PowerPoint: SQL 2
PowerPoint: Advanced
Analytics – Introduction
Jeremy Shafer
MIS2502
6/3/15
6/8/15
6/10/15
6/15/15
6/17/15
Syllabus
4
8
4
8
Analysis Scenario: Determining customer behavior
based on a profile (decision trees)
In-class exercise: Interpreting Decision Tree Output
4
8
In-class exercise: Decision trees in SAS Enterprise Miner
5
9
Analysis Scenario: Identifying similar customers
(clustering and segmentation)
5
9
In-class exercise: Interpreting Clustering Output
5
9
5
10
In-class exercise: Clustering and Segmentation in SAS
Enterprise Miner
Analysis Scenario: What products are purchased
together? (Association Rules)
5
10
5
10
6
11
Principles of Data Visualization
6
11
In-class exercise: Data Visualization
6
12
Final Exam
Page 6
PowerPoint: Classification
using Decision Trees
PowerPoint: Clustering and
Segmentation
PowerPoint: Association
Rule Mining
In-class exercise: Interpreting Association Rule Mining
Output
In-class exercise: Association Rule Mining in SAS
Enterprise Miner
PowerPoint: Principles of
Data Visualization
* Friday 5/15/2015 - Last day to add or drop a course
** Monday 6/1/2015 - Last day to withdraw from a course
Spring 2015
Jeremy Shafer