Welcome to DSC 433/533 - Information Analysis for Managerial Decisions, offered by the Department of Decision Sciences in the Lundquist College of Business at the University of Oregon: MW 8:00-9:50am in 232 Lillis.
Computer-based collections of data are widely used to support managerial decision-making, and in recent years technology advances have seen such data collections increase both in size and complexity. Large collections of data, however well structured, may contain concealed patterns of information that cannot be readily detected. Nevertheless, managers must learn how to leverage this information to make profitable business decisions. Over time, firms rely increasingly upon fact-based decision making approaches, requiring that managers understand how to develop defensible business proposals based on both spreadsheet and database analysis.
This course examines the business case for the use of data-driven analytical tools for enhancing decision-making and managing risk. By understanding and applying appropriate business models and data-driven analytical tools, we learn how analysts and managers can uncover new strategies for serving customers and increasing profits. We will investigate the effectiveness of data-analysis techniques that are considered useful in business applications, and, in particular, the applicability of data mining and other "knowledge discovery" methods.
The instructor for this course is Iain Pardoe. Please send your course questions to ipardoe at lcbmail.uoregon.edu. The course website is http://lcb1.uoregon.edu/ipardoe/teaching/dsc433.
The views and opinions expressed in this page are strictly those of the page author. The contents of this page have not been reviewed or approved by the University of Oregon.