Data analysis and visualization using Business Intelligence tools

In today’s rapidly changing data-driven economy, understanding modern analytical tools and the ability to adapt to innovative technologies such as GenAI is crucial to developing competitive competencies, achieving market advantage and providing important decision-making information across industries. The open lecture led by Ihor Muzyka, Head of Analytics at the Żabka Group, was an opportunity to learn more about how the choice of role and position affects the development of a career path in analytics, which data analysis tools are chosen by modern organizations, whether and how GenAI can help us with ongoing analytical tasks.

During the lecture, students acquired knowledge of skills in interpreting and processing complex data sets, which is crucial in today’s information-dominated world. This knowledge will allow to better understand how data can be used to make better business decisions, forecast market trends and optimize processes. Business Intelligence (BI) tools enable effective data visualization, which makes it easier to understand and communicate conclusions to various recipients. Additionally, discussing the role of tools based on generative artificial intelligence (GenAI) in data analysis opens perspectives on their applications in automating and improving analytical processes. Such competencies are important in various sectors of the economy, where the ability to effectively use data determines competitiveness and innovation.

Żabka Group has achieved a leading position in the market thanks in part to a fundamental change in its business strategy, which it has moved from a primarily intuition-based approach to data-driven decisions. Currently, the company is focused on offering customers services that are not only convenient, but also fast, putting their time first. The Żabka Group consists of many units, the largest of which are Żabka Polska, Żabka Digital and Żabka Future.

The lecture took place on January 22, 2024. The event was organized by the SRG Data Science.