Data Analytics

4 credit hours

In today's technology-enabled world, organizations collect a wealth of information as a part of their business operations. The past decade has seen an explosion in the amount of business data, their types, and their sources. For example, manufacturers track their production and shipments at stock-keeping-unit level, retailers record all customer transactions across different channels, grocery stores maintain scanner panel data, market research firms maintain representative household panels, content providers track DVR and Web usage, social media sites record user interactions in detail, service firms measure customer feedback, and online media stores and serves text, video, and audio data. Today firms are grappling with data overload while trying to extract valuable information, trends, and patterns from their terabytes of data.

This course introduces tools, software, and approaches for harnessing this data and information to drive effective managerial decision making, specifically how to visualize data, how to understand patterns and relationships in data, how to fit and validate predictive models, how to analyze consumer choice behavior, how to market a new product, how to design experiments to acquire new data, and how to manage a data-driven organization. We will practice these skills with hands-on analyses of real datasets. We will draw from a multidisciplinary set of examples, although we will emphasize marketing examples due to the availability of interesting datasets in that domain.

Watch the below video for a brief introduction to the Data Analytics course:

Explore how you can customize your degree by selecting from wide-ranging concentrations of study that focus on specialized disciplines. You can also request information to learn more.