Business Knowledge Series course
Presented by Wouter Verbeke, Ph.D., assistant professor of Business Informatics at the University of Brussels (Belgium). His research is situated in the field of predictive analytics for business applications, such as customer relationship management and credit risk modeling. His work has been published in international scientific journals such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Software Engineering, European Journal of Operations Research, International Journal of Forecasting and Expert Systems with Applications. He teaches several courses on information systems and advanced modeling for decision making to business students, and regularly tutors courses on credit risk modeling and customer analytics to business professionals. He previously worked in the risk analytics department of a large international bank, and was a lecturer at the University of Edinburgh Business School (UK). More information can be found at www.wverbeke.net.
Many companies are flooded with huge amounts of data available in corporate databases and/or data warehouses. A key challenge is how to optimally manage this data overload and use analytics to better understand, manage, and strategically exploit the complex dynamics of customer behavior.
This class starts by giving an overview of the steps involved when working out an analytics project in a practical business setting. After discussing the key data preprocessing activities, this course elaborates on how you can efficiently use and deploy both predictive and descriptive state-of-the-art analytics to optimize and streamline your strategic business processes such as marketing campaigns and/or risk management.
Examples of business applications that are covered include credit scoring and risk modeling, customer retention and response modeling, market basket analysis and cross-selling, customer lifetime value modeling, and Web intelligence and social network analytics.
You receive extensive practical advice and guidelines on how to put all the analytical tools and concepts to work in a real-life setting. The class focuses on analytical concepts, techniques, and methodologies and their applications.
Software demonstrations illustrate and clarify the concepts, but no hands-on use of software is included.
The class includes self-study sections with additional real-life case studies.
Learn how to
- develop high-performing analytical business models using state-of-the-art analytics and data mining
- get more in-depth knowledge about your customer equity using analytics
- optimally prepare and enrich your data as a key ingredient to powerful analytics
- predict customer behavior using regression and decision tree approaches
- describe customer behavior using association rules, sequence analysis, and clustering
- use social network data and analytics to better understand and manage collective customer dynamics
- put analytics to work in a practical business setting.
Who should attend
Business analysts, senior data analysts, quantitative analysts, data miners, senior CRM analysts, marketing analysts, risk analysts, analytical model developers, online marketers, and marketing modelers in the following industries: banking and finance, insurance, Telco, on-line retailers, advertising, Pharma
Kurset afholdes på engelsk
Before attending this course, you should have a basic background in statistics.
This course addresses None software.