This thesis explores the role of Artificial Intelligence in supporting Advanced Analytics practices, focusing on its applications in business decision-making processes. After analyzing the context and the main technologies involved, the benefits that AI can offer are examined, including the improvement of predictive analysis, the generation of deeper insights, and the optimization of Business Intelligence processes. Through case studies and empirical analysis, the research highlights how the integration of these tools can enhance the efficiency and quality of business analytics. Finally, the limitations and challenges of AI adoption, such as model interpretability and ethical implications, are discussed. The results suggest that, if properly implemented, this technology represents a key factor for the future of advanced analytics.
Questa tesi esplora il ruolo dell'Intelligenza Artificiale nel supporto alle pratiche di Advanced Analytics, con un focus sulle sue applicazioni nei processi decisionali aziendali. Dopo un'analisi del contesto e delle principali tecnologie coinvolte, vengono esaminati i benefici che l’AI può offrire, tra cui il miglioramento dell’analisi predittiva, la generazione di insight più approfonditi e l’ottimizzazione dei processi di Business Intelligence. Attraverso casi studio e analisi empiriche, la ricerca evidenzia come l’integrazione di questi strumenti possa aumentare l’efficienza e la qualità delle analisi aziendali. Infine, vengono discussi i limiti e le sfide nell’adozione dell’AI, come l’interpretabilità dei modelli e le implicazioni etiche. I risultati suggeriscono che, se implementata correttamente, questa tecnologia rappresenta un fattore chiave per il futuro dell’analisi avanzata.
L'Intelligenza Artificiale a supporto degli strumenti di Business Intelligence
MARTINI, ELISABETH
2024/2025
Abstract
This thesis explores the role of Artificial Intelligence in supporting Advanced Analytics practices, focusing on its applications in business decision-making processes. After analyzing the context and the main technologies involved, the benefits that AI can offer are examined, including the improvement of predictive analysis, the generation of deeper insights, and the optimization of Business Intelligence processes. Through case studies and empirical analysis, the research highlights how the integration of these tools can enhance the efficiency and quality of business analytics. Finally, the limitations and challenges of AI adoption, such as model interpretability and ethical implications, are discussed. The results suggest that, if properly implemented, this technology represents a key factor for the future of advanced analytics.| File | Dimensione | Formato | |
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TESI MAGISTRALE_MARTINI ELISABETH.pdf
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https://hdl.handle.net/20.500.12608/84926