代写INTG1-GC1025 DATABASE MANAGEMENT & MODELING Fall 2024代做留学生Matlab编程

DATABASE MANAGEMENT & MODELING

GENERAL COURSE INFORMATION:

Course number and section: INTG1-GC1025 section 002

Credits: 3

Semester/Year: Fall 2024

COURSE DESCRIPTION

In this course, students learn the basics of database set up and management as well as the analytical techniques and tools used in integrated marketing to assess, enhance, and profit from customer-relationship management.  The course reviews database technology, organization and planning including technology needs and outsourcing considerations; sampling techniques such as nth selects and frozen files; creating powerful predictor variables such as univariate and cross tabulations, ratios, time series variables, and other measures. The course also covers predicting customer actions by using multiple linear regression and logistic regression to model response, payment, attrition, churn, and other factors that assist in segmentation. Students also learn how to combine prospect and customer data residing on databases with outside sources of data to drive response models.

COURSE PREREQUISITES:

None.

COURSE STRUCTURE/METHOD:

To meet our learning outcomes, this course is structured around various content, activities and assignments each week.  In addition to the In Class Topics we will cover, which are outlined in the syllabus, each week you will see what work you need to Prepare, what assignments and assessment let you Demonstrate your knowledge and mastery, additional information to Explore and some questions to help you Reflect on your learning and experience each week.

· PREPARE: contains learning materials that the instructor would like you to review and engage with in preparation for this session. This may include readings, videos to watch, podcast to listen to, blogs to review etc.

· DEMONSTRATE: contains activities, principally assignments and assessments that provide you an opportunity to demonstrate your understanding and mastery of the knowledge, skills and abilities covered in class, in support of the learning outcomes.  This is where the instructor will post the weekly assignments including the work to be graded (and links to the Assignments Section within Brightspace/LMS) 

· EXPLORE: contains learning materials and activities which you can explore if you wish to delve further into any of the topics covered in the session. These are not required but optional and will add value to your broader or deeper understanding of the topics covered in the session. 

· REFLECT:  contains questions, prompts, ideas which may help you reflect on your learning and experience in this session or more broadly in the course. A key part of effective learning is developing the cognitive skill of reviewing what you have learnt, contextualizing your learning, making links with other topics you are studying and with your own experience. These reflections are typically not graded, but an opportunity for you to deepen your learning.

· Course delivery format in Brightspace See Course as “ASSESSMENT STRATEGY” below

· Meeting frequency: weekly

· Organization of the course includes lecture, discussion, team projects.  

· Brightspace is the learning management system

COURSE LEARNING OUTCOMES:  

· Design sampling techniques and predictive variables for marketing analyses to identify marketing opportunities 

· Analyze data for new and existing customer segmentations to drive marketing recommendations 

· Create predictive analytical models, charts and profit calculations to evaluate viable target audience segments for program and product launches 

· Recommend data-driven strategies to improve response, sales, and financial outcomes of integrated marketing plans 

· Use analytical tools and processes to drive successful marketing outcomes 

· Create a unique database, based on the theory of database creation and connectivity, between various siloed data sets

COMMUNICATION POLICY:

Office Hours: Thurs., 5:30-6:29 PM EST, by phone or conference. First, make an appointment by email.

Please use NYU email and/or the announcements/email function within Brightspace for all communications with students to both protect student privacy and meet the FERPA Guidelines.  

Students have the opportunity to add their pronouns, as well as the pronunciation of their names, into Albert. Students can have this information displayed to faculty in Albert, Brightspace, and other NYU systems. Students can also opt out of having their pronouns viewed by their instructors.

COURSE EXPECTATIONS:

Classes will begin with discussions of homework previously assigned. Students may be randomly called upon to participate in discussion of homework and reading assignments. Following these discussions, the instructor will begin the outlined lesson, including in-class exercises. Exams will be administered as specified in the “Course Outline” to be handed available below.

Attendance

Students are required to attend all classes. Per University policy, excused absences are only granted in cases of documented serious illness, family emergency, religious observance, or civic obligation. In the case of religious observance or civic obligation, this should be reported no later than the first week of class.  Recruiting activities, job interviews and incompatible travel plans, for example, are considered unexcused absences even if notification is given in advance. Unexcused absences from sessions will have a negative impact on your final grade. A student who has three unexcused absences may earn a Fail grade. For each absence, a third of a grade (3 points) will be deducted, e.g. a B could become a B-

 Students are responsible for assignments given during any absence. The current assignments will be displayed on the NYU website.

Students will receive credit for attendance only when they arrive to class on time and stay to the end of the class period. Students may enter the Zoom meeting room late or leave class early only if given permission by the instructor.

University Calendar Policy on Religious Holidays:   http://www.nyu.edu/about/policies-guidelines-compliance/policies-and-guidelines/university-calendar-policy-on-religious-holidays.html 

There will be penalties for late assignments [submission after we have reviewed it in class will not count].

As graduate students, you are expected to conduct yourselves in a professional manner and engage and collaborate with your classmates. SPS classrooms are diverse and include students who range in age, culture, learning styles, and levels of professional experience. To maintain an inclusive environment that ensures all students can equally participate with and learn from each other, as well as receive feedback and instruction from faculty during group discussions in the classroom, all course-based discussions and group projects should occur in a language that is shared among all participants.

Students who join the course during add/drop are responsible for ensuring that they identify what assignments and preparatory work they have missed and complete and submit those per the syllabus.

Students who plan to miss classes for religious reasons are expected to inform. instructors beforehand and to be responsible for assignments given during their absence. For university policies on religious holidays please check:

https://www.nyu.edu/about/policies-guidelines-compliance/policies-and-guidelines/university-calendar-policy-on-religious-holidays.html

Makeup assignments for excused absences: You should find out what was covered in the missed session by speaking to a fellow classmate and checking the Brightspace course site to review all the resources provided by your instructor. Contact your instructor regarding makeup assignments that may be provided to you.

Assignments:

All students must complete all course assignments. You should come to each class fully prepared, having read the assigned readings and completed the assignment(s), and actively engage in class discussions.

All assignments must be uploaded to the folders on Brightspace posted under the “Assignments” tab. Each assignment folder will include the detailed assignment description and grading criteria/rubric. The number of the assignments and their due dates are on the course outline that follows. Assignment due dates are final and non-negotiable. Late assignments are not accepted without prior written permission from the faculty and cannot be granted more than once throughout the semester. Failure to submit assignments on time will result in a grade reduction equal to the credit for that assignment.