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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: • • • • • • • 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: • • • • • 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