Information Analysis for Managerial Decisions (DSC 433 / DSC 533)
Information technology advances yield an ever-increasing volume of data to support managerial
decision making. The use of computer-based collections of data to support business
decision-making activities has been commonplace since the early 1970s, and in recent years the
digital revolution has seen such data collections increase both in size and complexity. Managers
must learn how to leverage this information to make profitable business decisions. Collections of
data, however well structured, may contain concealed patterns of information that cannot be
readily detected.
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. In this course, 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. This course
examines the business case for the use of data-driven analytical tools for enhancing
decision-making and managing risk.
