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Shannon Mc Mahon
Anomaly Detection and Notification in Google Analytics Data.
Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2023
Abstract: |
Carried out in collaboration with Digital Pills, this thesis aims at developing a product that detects anomalies in data gathered by Google Analytics and communicate them to the owner of such Analytics account. In this document we will firstly give a brief overview of Google Analytics and how it falls under the scope of the GDPR. Subsequently we dive into more technical aspects and see what metrics and dimensions are useful to monitor, as well as how the infrastructure that collects the data is setup on Google Cloud Platform in order to be scalable. Lastly, The notification system to alert clients of detected anomalies is discussed, together with details of the anomaly detection algorithm and possible improvements that will guide future version releases of the tool. |
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Relatori: | Paolo Garza |
Anno accademico: | 2022/23 |
Tipo di pubblicazione: | Elettronica |
Numero di pagine: | 69 |
Informazioni aggiuntive: | Tesi secretata. Fulltext non presente |
Soggetti: | |
Corso di laurea: | Corso di laurea magistrale in Data Science And Engineering |
Classe di laurea: | Nuovo ordinamento > Laurea magistrale > LM-32 - INGEGNERIA INFORMATICA |
Aziende collaboratrici: | DIGITAL PILLS S.R.L. |
URI: | http://webthesis.biblio.polito.it/id/eprint/26880 |
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