Alessio Vacca
Design and implementation of a Business Intelligence pipeline for Poste Italiane.
Rel. Eliana Pastor. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2023
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Abstract: |
The growing amount of data generated by companies in today’s digital age has led to an increased demand for tools and techniques that can help organizations make informed decisions based on data-driven insights. For this reason, more and more companies are deciding to rely on consulting firms to help them create and manage systems that can measure and understand business performance and make them available to their users. In this context, business intelligence (BI) and data analytics have become crucial for organizations that want to gain a competitive advantage in their industry, enabling them to extract valuable insights from data and use them to optimize their operations, improve customer satisfaction, and drive growth. This thesis project arises from the collaboration between Advant s.r.l and Poste Italiane S.p.A. The first is a consulting IT company, mostly dedicated to data analysis and Business Intelligence, the latter is a well-known Italian public company, which is responsible for managing postal, banking, financial, logistics, and telecommunication services. In this context, I have been involved in the design and implementation of a BI system that supports decision-making and strategic and monitoring activities for its users within the sales force departments, in order to provide evidence to the salespeople operating in the territory. In particular, the project involved the analysis of the revenues and volumes from auxiliary services related to parcel products sold. The entire development pipeline is based on cloud technologies from Microsoft’s Azure suite. It includes a back-end part consisting of a data mart model built on top of the provided data source, after an initial phase of functional and user requirements analysis. Subsequently, an ad hoc ETL process was designed to automatically feed the target data storage, so as to update the dashboards containing the required reports and make them available to the end users. My contribution was then integrated into a larger project, with which it shares some technical features. |
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Relators: | Eliana Pastor |
Academic year: | 2023/24 |
Publication type: | Electronic |
Number of Pages: | 77 |
Subjects: | |
Corso di laurea: | Corso di laurea magistrale in Data Science And Engineering |
Classe di laurea: | New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING |
Aziende collaboratrici: | ADVANT S.R.L. |
URI: | http://webthesis.biblio.polito.it/id/eprint/28498 |
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