Study data-driven business intelligence challenges and tools such as data mining and machine learning techniques and apply data-driven intelligence to improve decisions and estimate the expected impact on performance.
Across industries, routine decisions and competitive strategies increasingly rely on data-driven business intelligence. Unprecedented volumes of rich data can now be analyzed to predict the consequences of alternative courses of action and guide decision-making. The urgency to utilize data-driven intelligence spans industries, and this class provides an introduction to data-driven business intelligence challenges and tools like data mining and machine-learning techniques.
- Machine learning
- Applications to business
- Data mining
- Effectively apply data-driven intelligence to improve your decisions and systematically estimate the expected impact on relevant performance objectives.
- Understand the landscape of data-driven intelligence tools, the basics of data mining techniques, and their applications in practice
- Develop a data-analytical approach to problem-solving so as to be able to identify opportunities to derive value from data-driven intelligence
- Acquire some hands-on experience so as to follow up on ideas or opportunities that present themselves
Maytal Saar-Tsechansky, Ph.D., Associate Professor, Department of Information, Risk, and Operations Management