COMM 414 – Data Visualization and Business Analytics
Business professionals must have familiarity with and skills in each of descriptive, predictive and prescriptive analytics. Descriptive analytics includes data analysis and data visualization: understanding, manipulating, evaluating and presenting the many complex data and information streams that drive today’s businesses and organizations. Predictive analytics includes forecasting, various statistical techniques, data mining, and machine learning; taking the analysis of the present to generate likely scenarios of the impact of doing things differently or of future trends. Prescriptive analytics involves the employment of a number of analytical models to aid decision making: included but not limited to would be optimization, Monte Carlo simulation, decision trees and discrete event simulation.
The increasing use of business analytics throughout business suggests that non-OpLog option students might wish to improve their exposure to business analytics by adding this course to their degree program. A course goal is to also be accessible to such students. For example, the analytics areas mentioned above would be of interest to many students seeking a career in finance, marketing, or consulting.
Upon successful completion of this course, students will be able to:
Know real-world business analytics examples across multiple industries.
Be able to perform terabyte-size data queries and aggregations with Google BigQuery.
Be able to create effective data visualizations with Tableau.
Be able to build and estimate regression and basic machine learning models, and perform data simulations and optimizations with R.
Undertake a wide range of business analytics projects.
Generate business insights from business analytics outcomes.
Prerequisite: One of COMM 204, COMM 399.