Course Number: 95-852
Today's enterprise is a complex system spanning a variety of corporate functions aimed at achieving a range of convoluted objectives. Its environment is subject to globalization and to the effects of the "era of information". Its management is therefore exposed to a formidable task of analyzing huge amounts of time-critical information and, nonetheless, it is expected to always make the right decisions at the right times. Conveniently, a range of technologies and products cumulatively known as Business Intelligence (BI) come to the rescue.
The BI solutions therefore aim at two main goals: firstly, at optimizing the efficiency of decision making by human managers, and secondly, at maximizing the utilization of the available data (so that no important clue is ever missed). The term of BI is used in reference to a variety of tasks (such as reporting, monitoring, alerting, data aggregation, ad-hoc querying, forecasting), function-specific applications (such as enterprise resource planning, enterprise risk modeling, customer relationship management, corporate dashboards and so on), as well as underlying technologies (including computing hardware, telecommunication infrastructure, database management, data warehousing, data mining and so on). The analytic component of BI attracts a growing attention of their current and prospective users. The trend stems from the attainable competitive advantage which can be realized by effectively using of analytics in the context of the generally defined Business Intelligence.
This course focuses on the analytic component of the BI in the context of its practical application. It combines an introduction of selected analytic and data representation techniques specifically useful in the context of BI (introduced at the practical and non-highly-mathematical level), with extensive in-class discussions, case studies and readings related to recent real-world deployments of BI analytics. The regular meetings will be complemented with talks by a few guest speakers, selected among seasoned and successful practitioners of Analytics and Business Intelligence.
The participants will have a chance to gain and solidify knowledge of the most important contemporary methods of analytics, and to develop understanding of practical applicability of studied technologies in a variety of business scenarios. The students will learn how to formulate analytic tasks in support of business objectives, how to define successful projects, and how to evaluate utility of existing and potential applications of discussed technologies in practice.
95-791 Data Mining I 6 Credits