BUSM 2320 - Business Analytics for Data Driven Decisions

Academic Division: Business, Industry and Technology
Academic Discipline: Business Administration

Course Coordinator: Carmen Morrison
Assistant Dean: Vincent Palombo, PhD

3 Credit(s)
An understanding of data is fundamental to success in the digital age of business. This course provides the theoretical foundation of data analytics as well as the application of data analysis tools. Students will develop competencies to structure data and use data mining techniques in response to business scenario queries. Students will experience how businesses rely on data analysis every day to make relevant, data-driven decisions. Through projects and simulations, this course enables students to apply their technical skillsets to real-world business situations.

Required Prerequisite Course(s): BUSM 2010 and CISS 1290

Student Learning Outcomes for Course

Demonstrate working knowledge of programming tools, structured query language to execute data collections, analysis and visualization processes and techniques	Assessed through quizzes, exercises, and projects/simulations throughout the semester and final exam.
Evaluate business queries and choose the appropriate tools and techniques of business analytics	Assessed through exercises and projects/simulations throughout the semester but primarily during weeks 1-4 and final exam.
Organize field experiments in digital environments using A/B testing	Assessed through exercises and projects/simulations throughout the semester but primarily during weeks 5-8 and final exam.
Develop an understanding of machine learning and deep learning as part of artificial intelligence	Assessed through quizzes during weeks 5-8 and final exam.
Evaluate opportunities to use cloud services and Internet of Things in business analytics	Assessed through quizzes, exercises, and projects/simulations during weeks 9-12 and final exam.
Create web and business analytics solutions using concepts of optimization and attribution for better decision-making	Assessed through quizzes, exercises, and projects/simulations during weeks 9-15 and final exam.
Create predictive and prescriptive models for business scenarios	Assessed through quizzes, exercises, and projects/simulations during weeks 12-15 and final exam.

Topics:
Topic 1: Business Analytics Overview (weeks 1-4)

Topic 2: Spreadsheet and Programming Tools for Business Analytics (weeks 1-4)

Topic 3: Unstructured Data and NoSQL (weeks 1-4)

Topic 4: Structured Data and SQL (weeks 1-4)

Topic 5: Data Mining with Cluster Analysis (weeks 5-8)

Topic 6: A/B Testing Essential Business Factors (weeks 5-8)

Topic 7: Machine Learning and Deep Learning (weeks 5-8)

Topic 8: Cloud Services (weeks 9-12)

Topic 9: Web Analytics (weeks 9-12)

Topic 10: Analytics for the Internet of Things (weeks 9-12)

Topic 11: Storytelling through Visualization (weeks 9-12)

Topic 12: Metrics (weeks 13-15)

Topic 13: Predictive Analytics (weeks 13-15)

Topic 14: Optimization (weeks 13-15)
Assignments:
At a minimum, the following activities will be part of every offering of this course:

Assigned readings from the text
Homework and/or Exercises
Class Participation
Simulations and/or Projects
Quizzes/Exams

Standard Grading Scale
93-100 A

90 - 92 A-

87- 89 B+

83 - 86 B

80 -82 B-

77- 79 C+

73 - 76 C

70 -72 C-

67- 69 D+

63 - 66 D

60 -62 D-

00- 59 F

Statement on Diversity
NC State College believes that every student is a valued and equal member of the community.* Every student brings different experiences to the College, and all are important in enriching academic life and developing greater understanding and appreciation of one another. Therefore, NC State College creates an inclusive culture in which students feel comfortable sharing their experiences. Discrimination and prejudice have no place on the campus, and the College takes any complaint in this regard seriously. Students encountering aspects of the instruction that result in barriers to their sense of being included and respected should contact the instructor, assistant dean, or dean without fear of reprisal.

*Inclusive of race, color, religion, gender, gender identity or expression, national origin (ancestry), military status (past, present or future), disability, age (40 years or older), status as a parent during pregnancy and immediately after the birth of a child, status as a parent of a young child, status as a foster parent, genetic information, or sexual orientation.

Standard NCSC Course Policies
Important information regarding College Procedures and Policies can be found on the syllabus supplement located at http://catalog.ncstatecollege.edu/m

TEXTBOOK INFORMATION
TEXTBOOK: Business Analytics: Business Analytics/Mimic Analytics Publisher: Stukent ISBN: 9781734688832