![](/style/images/tocco.png)
Gabriele Bruno Franco
Insightfully: from ETL to analytics product to obtain actionable insights.
Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2023
Abstract: |
This thesis was aimed at the developing a website that creates value by extracting data from third party APIs, such as, Facebook and Instagram, Linkedin Paid and Organic, both paid and organic as social media platforms, Google Analytics 4 as a leading marketing analytics platform, Mailchimp and Activecampaign as Direct Email Marketing platforms. Once extracted, the extracted data is then loaded in a three-layer database schema, Gold / Silver / Bronze, as per the Medallion Schema. From the Gold layer, the data is then visualized and explored from a front-end application built in HTML, CSS and Javascript. Specifically, using the React framework and the Material-UI library in order to build custom graphs, tables and widget to be used by the end user. The end user is expected to be non-technical, as the ideal target is a marketing manager or operation person that needs to explore, understand and take decisions on current and past campaign, dem and social media data in order to better understand and predict future performances. The thesis work was carried out in a company, Digital Pills. As such, the document is focused on how the development processes were handled in order to create a sustainable product for the company as well as deep dives on technical decisions, down to the code-level. Many Google Cloud Platform services, are explored in detail as well as a few competing services that were considered during the development process of the product as viable alternatives. |
---|---|
Relatori: | Paolo Garza |
Anno accademico: | 2022/23 |
Tipo di pubblicazione: | Elettronica |
Numero di pagine: | 62 |
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/26814 |
![]() |
Modifica (riservato agli operatori) |