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.

Learning objectives

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.

Course credits:
3

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