dc.contributor.advisor |
Pelizzon, Loriana |
it_IT |
dc.contributor.author |
Vitulano, Andrea <1998> |
it_IT |
dc.date.accessioned |
2022-06-27 |
it_IT |
dc.date.accessioned |
2022-10-11T08:26:59Z |
|
dc.date.available |
2023-12-06T13:52:27Z |
|
dc.date.issued |
2022-07-11 |
it_IT |
dc.identifier.uri |
http://hdl.handle.net/10579/21878 |
|
dc.description.abstract |
Big data has proven to be one of the most strategic assets for companies and institutions in recent years. Many refer to big data as the “fuel” of the digital economy and the statistics seem to confirm that. With an estimated market size of billions of dollars , big data positions among the most important markets worldwide. The reason of such importance is that nowadays, most of the internet activity is based on online advertising and product/service purchase. The nature of advertising is switching from mass communication to highly-tailored ads based on the interest and features of the target audience. Tailored advertising requires a process called “profiling” which is a data-intensive activity aimed at categorizing each user into pre-defined “profiles”. Companies and entities who gather and exploit data in an intensive manner are the one which are able to gain and sustain a key competitive advantage. Through intensive data exploitation, companies are able to better understand the interest and preferences of their customers. Moreover, thanks to profiling activities, whole new business models are being created based on personalized advertising.
In this thesis, we will analyze the big data environment under different aspects and with different purposes. The final goal is to understand the importance of big data in the digital economy, to analyze the issues and concerns which may arise, to explore possible fruitful integration with other technologies, and to learn about data monetization.
In the first chapter is introduced the big data environment, its definition, purposes, and key aspects. Moreover, the process of data gathering is analyzed together with an analysis of the main data giants. With respect to data giants, we will learn how big data allowed new business models to work properly and how companies convert user’s data in revenues.
The second chapter is more focused on threats and concerns regarding big data exploitation, we will analyze the “Cambridge Analytica” case study. Together with the issues we will discuss the main regulations which concerns big data and user privacy. We will adopt both a European and American perspective, in order to provide a full overview of the regulation environment.
In the third chapter we will analyze the integration between big data and blockchain technology. To do that, we will devote the first sub-chapter to blockchain introduction and definition. Consequently, we will discuss the main advantages that occur between the integration of big data and decentralized technology.
Finally, the last chapter will discuss about big data monetization and will analyze a case study of a British project called HUDI (Human Data Income). Such project aims at decentralizing the ownership of data by letting the data owners decide which information to share and which not to. We will discuss how big data can be used to generate a passive/active income and how the cryptocurrencies environment is linked to such activity. |
it_IT |
dc.language.iso |
en |
it_IT |
dc.publisher |
Università Ca' Foscari Venezia |
it_IT |
dc.rights |
© Andrea Vitulano, 2022 |
it_IT |
dc.title |
The Big Data Environment: Opportunities, Threats, Blockchain integration and Monetization |
it_IT |
dc.title.alternative |
The big data environment: Opportunities, Threats, Blockchain integration and Monetization |
it_IT |
dc.type |
Master's Degree Thesis |
it_IT |
dc.degree.name |
Economia e finanza |
it_IT |
dc.degree.level |
Laurea magistrale |
it_IT |
dc.degree.grantor |
Dipartimento di Economia |
it_IT |
dc.description.academicyear |
2021/2022_sessione estiva_110722 |
it_IT |
dc.rights.accessrights |
openAccess |
it_IT |
dc.thesis.matricno |
885160 |
it_IT |
dc.subject.miur |
SECS-P/09 FINANZA AZIENDALE |
it_IT |
dc.description.note |
|
it_IT |
dc.degree.discipline |
|
it_IT |
dc.contributor.co-advisor |
|
it_IT |
dc.provenance.upload |
Andrea Vitulano (885160@stud.unive.it), 2022-06-27 |
it_IT |
dc.provenance.plagiarycheck |
Loriana Pelizzon (pelizzon@unive.it), 2022-07-11 |
it_IT |