Revolutionizing Business Strategy Application: Generative AI for SQL Mapping on GA4 Data

In today's digital landscape, efficient use of cloud infrastructure is crucial for businesses to stay competitive and meet evolving consumer demands. Cloud migration offers unmatched scalability, flexibility, and cost-effectiveness, helping organizations streamline operations and boost innovation. However, migrating complex systems to the cloud poses significant challenges, especially in optimizing data flow.This master's thesis examines cloud migration, clickstream data analytics, and integrating machine learning models to automate data mapping. It focuses on enhancing efficiency and performance for Company, a leading fashion enterprise aiming to leverage advanced technologies. The migration of Company's data infrastructure to the cloud sets the stage for this study, showcasing the balance between technological progress and business needs. With Google Analytics 4 (GA4) and its extensive clickstream data (user sessions), there is an urgent need to map this data according to Company's frequently updated marketing strategies.Traditional data mapping methods are labor-intensive and error-prone, slowing innovation and decision-making. To overcome these challenges, this thesis proposes using Language Model (LLM) to automate the mapping process, utilizing artificial intelligence to streamline operations and improve accuracy.By leveraging LLM models, this research aims to provide Company with a data-driven approach to cloud migration, ensuring seamless integration and optimal performance. Through an in-depth analysis of clickstream data, the study seeks to create a framework for efficient data flow optimization in the cloud environment.Ultimately, this thesis aims to enhance understanding of AI applications in addressing modern business challenges. By offering actionable insights and practical recommendations, the research strives to equip Company and similar enterprises with the tools and methodologies to thrive in the digital age.