Sandro Radovanović is an assistant professor at University of Belgrade, Faculty of Organizational Sciences. His research builds on designing and developing algorithmic decision-making models. More specifically, he designs and develops machine learning models and decision support systems. He is particularly interested in designing algorithmic decision-making systems that promote and/or enforce fairness and equality. Since May 2018, he has acted as a board of assistants member at Euro Working Group on Decision Support Systems. In addition, since December 2020 he has acted as a social media team member at Mechanism Design for Social Good. So far, he has published over 80 scientific papers in journals and conference proceedings. Besides being active in research, Sandro Radovanović has almost ten years of experience in designing and deploying business intelligence and machine learning solutions in practical settings.
Business Intelligence Solutions for Banking utilize the data sources that one bank could have (or obtain) with an idea to provide the decision-makers with a different point of view on the business performance. Business intelligence solutions enable users to connect to multiple and disparate data sources and display interactive dashboards that would normally require significant data modeling and database skills. Besides reducing the need for data modeling, the tools used in this summer school allow the creation of ad-hoc interactive dashboards that can help decision-makers inspect and explain the factors that influence the performance of a bank. The course will enable students to define and design key performance indicators and dashboards, as well as propose a data-driven solution to the problem at hand. Objectives: 1) Gain expertise on how to apply business intelligence solutions in the banking industry, 2) Basic understanding of data types, data modeling, and data querying, 3) Designing and developing data visualizations, reports, and dashboards. Outcomes: 1) Identify and analyze the situations where business intelligence can lead to better decision-making, 2) Design dashboards and ad-hoc reporting systems, 3) Apply business intelligence tools for data-driven decision-making 4) Communicate results to (non-technical) business users.
The workshop will provide students with hands-on experience in designing dashboards and ad-hoc reporting systems by applying Microsoft Power BI, a business intelligence tool for data-driven decision-making.