GDPR and data-driven strategy: is synthetic data an enabling solution?

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dc.contributor.advisor Rullani, Francesco it_IT
dc.contributor.author Rossato, Giovanni <1987> it_IT
dc.date.accessioned 2023-02-17 it_IT
dc.date.accessioned 2023-05-23T12:55:11Z
dc.date.issued 2023-03-13 it_IT
dc.identifier.uri http://hdl.handle.net/10579/22990
dc.description.abstract Big data is significantly changing the way companies can define their strategy and business model. Furthermore, the amount of data generated in the world has reached dimensions that were unthinkable until a few years ago. However, this important growth in sources, volumes, and velocity of data collected have also increased the storage and use of many private information (for example, personally identifiable information (PII)), thus increasing the vulnerability of privacy. There are many investments made by the healthcare sector, biomedical companies, advertising sector, private companies and government agencies in the collection, aggregation and sharing of huge amounts of personal data such as names, addresses, credit card numbers, etc. for the development of AIML systems that need to be protected. Big data can contain sensitive personal information that requires protection from unauthorized access and release. From a security point of view, the greatest challenge is to protect the privacy of individuals. Ensuring the privacy of people's data is mandatory under privacy laws. A possible solution for the protection of this data is anonymization, which consists of a process to protect privacy information by deleting or encrypting the identifiers that link a specific individual to the data generated. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Giovanni Rossato, 2023 it_IT
dc.title GDPR and data-driven strategy: is synthetic data an enabling solution? it_IT
dc.title.alternative GDPR and data-driven strategies it_IT
dc.type Master's Degree Thesis it_IT
dc.degree.name Data analytics for business and society it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Economia it_IT
dc.description.academicyear 2021/2022 - appello sessione straordinaria it_IT
dc.rights.accessrights closedAccess it_IT
dc.thesis.matricno 860282 it_IT
dc.subject.miur SECS-P/08 ECONOMIA E GESTIONE DELLE IMPRESE it_IT
dc.description.note none it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend 10000-01-01
dc.provenance.upload Giovanni Rossato (860282@stud.unive.it), 2023-02-17 it_IT
dc.provenance.plagiarycheck None it_IT


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