Advancing Data Analysis and Econometric Modeling
Ms. Viliyana Aleksieva from the Financial Stability Division of the Bulgarian National Bank shared her valuable reflections on the key takeaways from the "Data Science Using R for Data Analysis and Econometric Modeling" workshop held earlier this year. The event brought together central bank analysts from across institutions, addressing the growing need for quick, reliable analysis amidst challenges such as data quality and availability. Below, Ms. Aleksieva shares her experience and highlights the practical impact of the course on her day-to-day work.
"Working in the Financial Stability Division of the Bulgarian National Bank, I regularly handle large, diverse datasets to evaluate potential systemic risks in the banking sector. To better manage these responsibilities, I sought a structured opportunity to deepen my skills in R—a powerful tool for data analysis and econometric modeling. The workshop "Data Science Using R for Data Analysis and Econometric Modeling" perfectly aligned with my goals. What made it even more appealing was its in-person format, practical orientation, and manageable duration.
The course not only met but truly exceeded my expectations. From the very beginning, I appreciated its strong emphasis on practical application. Sessions were well-paced and packed with hands-on activities, from live coding to interactive exercises. A highlight was the group project at the end, where we applied newly acquired skills to a real topic of interest. The in-person nature of the course fostered meaningful interaction—not only with the incredibly knowledgeable instructors but also among fellow participants, enriching the overall learning experience.
The course content was exceptionally relevant to my day-to-day work. Sessions on data wrangling, exploratory data analysis, and econometric modeling laid a strong foundation. Advanced modules introduced techniques like machine learning, nowcasting, and, notably, the Shiny application—a tool I had no prior experience with. Choosing to focus on Shiny for the group project proved both challenging and rewarding. I discovered its potential for creating compelling visualizations and dynamic storytelling—skills that are highly valuable in my role.
Every component of the course had immediate professional relevance. I now feel more confident applying techniques like time series analysis, linear regression, and machine learning to better interpret financial data and model economic scenarios. The knowledge of Shiny, in particular, opens new doors for enhancing the way we communicate findings—both internally and externally—through interactive dashboards and visual narratives.
This workshop stands out as one of the most valuable learning experiences I’ve had in recent years. The organization was seamless, the content expertly delivered, and the atmosphere encouraging and collaborative. I highly recommend it to any colleague working in data-driven roles, particularly those in economics, finance, or policy analysis. It's a practical, insightful, and empowering experience—one that truly equips you to make more informed, impactful decisions in your work."