Download MIS2502.011 – Data Analytics Summer 2016 About the Instructor:

MIS2502.011 – Data Analytics
Summer 2016
About the Instructor:
Jeremy Shafer ([email protected])
209D Speakman Hall
Phone: (215) 204-6432
Profile: http://community.mis.temple.edu/jshafer
Office hours: 11:00am -1:00pm, Mondays and Wednesdays, 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 and Wednesday
On the web: http://community.mis.temple.edu/mis2502011summer2016
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, cuttingedge tools such as MySQL and R/R Studio.
Course Objectives:
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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.
MIS2502
Syllabus
Page 2
Required Textbook:
There is no required textbook for this course.
Evaluation and Grading:
Item
Percentage
Scale
Exams (2)
70%
94 – 100
A
73 – 76
C
Project
20%
90 – 93
A-
70 – 72
C-
87 – 89
B+
67 – 69
D+
Participation (see
“challenges” below)
10%
83 – 86
B
63 – 66
D
80 – 82
B-
60 – 62
D-
77 – 79
C+
Below 60
F
Once a grade is communicated to a student electronically, the student has a 1 week window in which
to approach the instructor and question the grade received. Grade adjustments of any sort will not be
considered after that 1 week window.
Exams:
There will be two exams during the semester. The date of the first exam is 6/1/2016 and the date of
the second exam is 6/15/2016.
Make-up exams will not be given under most circumstances. Exceptions are granted at the instructor’s
discretion and are typically limited to extreme circumstances such as documented hospitalization or
funeral attendance. If a student is permitted to take a make-up exam, the instructor reserves the right
to substitute an alternate exam with different content. Students may find the content of the make-up
exam to be more difficult than the original. It is, therefore, to a student’s advantage to show up for
each exam at the scheduled time and take it with the rest of the class.
Summer 2016
Jeremy Shafer
MIS2502
Syllabus
Page 3
Project:
In the class project, students will be asked to analyze a set of data and create a visual representation of
their findings. Students are to work in teams of 2 or 3. Each team member will receive the same
grade. Further details regarding the assignment will be released later in the semester.
Challenges and Participation:
There will be five challenges.
#
Topic
Due Date
1
SQL #1 – Getting Data out of the Database
MONDAY 5/23
2
SQL #2 – Putting Data into the Database
MONDAY 5/30
3
R #1 – Decision Trees
MONDAY 6/6
4
R #2 – Clustering
FRIDAY 6/10
5
R #3 – Association Rules
MONDAY 6/13
These challenges will be awarded a pass / fail grade. A “pass” is worth 1 point, a fail is worth 0 points,
and a challenge turned in late will not be awarded any points. Assignments are considered late if they
are turned in after noon on the day on which they are due. Challenges are used to determine the
students’ participation grade. (That is, if a student does all the challenges, and turns them in on time,
then that student’s participation grade will most likely be 100 %.)
Other factors *may* be considered when assigning a student participation grade. These factors
include:
• Did the student attend class regularly?
• Did the student thoughtfully contribute to course related conversations in class?
• Did the student work productively with his/her teammate(s) on the class project?
• Did the student’s conduct distract other students and/or impede their learning?
Submitting your work:
On the first day of class the instructor will require each student to set up a folder on owlbox (see:
owlbox.temple.edu) and share it with the instructor.
Students are to submit their challenges by copying files into that folder. The time / date stamp on the
files will be used to determine if they are on time or late.
Summer 2016
Jeremy Shafer
MIS2502
Syllabus
Page 4
Extra Credit and “Grading on the Curve”:
The instructor generally does not give extra credit opportunities. In the unlikely event that an extra
credit opportunity is offered, it will be made available to the whole class. Individual students will not
be offered extra credit opportunities as a way to compensate for poor academic performance earlier in
the semester.
If the instructor decides that a curve is necessary, it will be applied at the end of the semester, after all
graded items have been completed.
Classroom Etiquette:
The environment students create in class directly impacts the value gained from the course. To that
end, the following are some expectations regarding student conduct in class:
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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 the instructor) are speaking.
Attendance:
If a student misses all or part of class it is that student’s responsibility to catch up, talk to fellow
classmates; check the class blog, complete readings, etc. While every student is encouraged to visit the
instructor during office hours in order to gain a better understanding of material, 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 the
instructor’s discretion, and can range from a failing grade for the individual exam or project, to a failing
grade for the entire course, or to expulsion from the program.
Summer 2016
Jeremy Shafer
MIS2502
Syllabus
Page 5
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 Professional Achievement Requirement:
The MIS department has instituted a professional achievement points requirement for MIS majors.
Here are two excellent resources that describe why the points are important.
1. http://community.mis.temple.edu/current-students/professionalachievement
2. http://community.mis.temple.edu/store
Students are STRONGLY encouraged to, at a minimum, do the following to earn professional
achievement 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.
Schedule:
Keep in mind that all dates are tentative – check the Community site regularly for changes in the
schedule.
Date
Week Day
Topics
Course Materials
5/9/16
1
1
Course Introduction and Syllabus; The Information
Architecture of an Organization
PowerPoint: Information
Architecture
1
1
Data Modeling; Gathering requirements;
Introducing The Entity-Relationship Diagram
PowerPoint: Relational
Data Modeling
1
1
In-class exercise: Identifying entities and attributes
Summer 2016
Jeremy Shafer
MIS2502
5/11/16
*
Syllabus
Page 6
1
2
More on ERDs: Relationships, cardinality
1
2
In-class exercise: Creating an entity relationship
diagram
1
2
From ERDs to Schemas: Normalization, primary/foreign
keys, joins
In-class exercise: Converting ERDs to schemas
PowerPoint: Relational
Data Modeling
2
3
Getting data out of the database: SQL SELECT, DISTINCT
MIN, MAX, COUNT, and WHERE; Make sure you’ve
reviewed the MySQL PowerPoint prior to class, and also
worked though the assigned W3schools tutorial.
PowerPoint: SQL 1
2
3
Getting data out of the database: Joining tables, SQL
subselects, LIMIT
2
3
In-class exercise: Working with SQL, part 1
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
3
5
Principles of Data Visualization
3
5
In-class exercise: Data Visualization
3
5
Extract, Transform, Load (ETL)
PowerPoint: ETL
3
6
Turning transaction data into analytical data: Overview
of the Dimensional Model
PowerPoint: Dimensional
Data Modeling
3
6
The structure of the Dimensional Model: The Star
Schema
3
6
In-class exercise: Pivot Tables in Excel
3
6
Analysis Scenario: Determining customer behavior
based on a profile (decision trees)
PowerPoint: Classification
using Decision Trees
5/30/16
**
4
7
MEMORIAL DAY – NO CLASS
Introduction to Advanced
Analytics and R/ R Studio
(RECORDED LECTURE)
6/1/15
4
8
EXAM 1
4
8
In-class exercise: Interpreting Decision Tree Output
5/16/16
5/18/16
5/23/16
5/25/16
Summer 2016
PowerPoint: Relational
Data Modeling
PowerPoint: SQL 2
PowerPoint: Principles of
Data Visualization
Jeremy Shafer
MIS2502
Syllabus
4
8
In-class exercise: Decision trees
5
9
Analysis Scenario: Identifying similar customers
(clustering and segmentation)
5
9
In-class exercise: Interpreting Clustering Output
5
9
In-class exercise: Clustering and Segmentation
6
10
Analysis Scenario: What products are purchased
together? (Association Rules)
6
10
In-class exercise: Interpreting Association Rule Mining
Output
6
10
In-class exercise: Association Rule Mining
6/13/16 6
11
Review
6/15/16 6
12
Final Exam
6/6/16
6/8/16
Page 7
PowerPoint: Clustering and
Segmentation
PowerPoint: Association
Rule Mining
* Friday 5/13/2016 - Last day to add or drop a course
** Tuesday 5/31/2016 - Last day to withdraw from a course
Summer 2016
Jeremy Shafer