Varnost poslovnih podatkov pri implementaciji inteligentnega sistema chatgpt

Koleva, Marija

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Title:	Varnost poslovnih podatkov pri implementaciji inteligentnega sistema chatgpt
Authors:	ID Koleva, Marija (Author) ID Kljajić Borštnar, Mirjana (Mentor) More about this mentor...
Files:	UN_Koleva_Marija_2024.pdf (1,04 MB) MD5: 6DA4331E275A86E5A6C4D872D88569D4
Language:	Slovenian
Work type:	Bachelor thesis/paper
Typology:	2.11 - Undergraduate Thesis
Organization:	FOV - Faculty of Organizational Sciences in Kranj
Abstract:	Namen diplomske naloge je bil raziskati implementacijo in uporabo generativnih modelov, predvsem modelov generative pre-trained transformer (GPT), v poslovnem okolju podjetja X in razumeti njihov vpliv na poslovne procese. S poudarkom na varnosti in produktivnosti smo preučili prednosti in izzive integracije teh tehnologij ter opredelili ključne ugotovitve, ki vključujejo izboljšano učinkovitost, inovativnost, kakovost storitev in varnost podatkov. Uporabljene metode vključujejo študijo primera, intervju z vodjo projekta, analizo podatkov in pregled literature. Glavni zaključki vključujejo poudarek na potrebi po implementaciji varnostnih protokolov, upoštevanju etičnih vidikov in implementaciji najboljših praks pri implementaciji generativnih modelov. Priporočila vključujejo uporabo robustnih varnostnih mehanizmov, optimizacijo poslovnih procesov in nadaljnje raziskovanje možnosti uporabe generativnih modelov v poslovnem okolju.
Keywords:	generativni modeli, GPT, poslovno okolje, varnost, produktivnost
Place of publishing:	Maribor
Year of publishing:	2024
PID:	20.500.12556/DKUM-90247
COBISS.SI-ID:	210103043
Publication date in DKUM:	03.10.2024
Views:	122
Downloads:	61
Metadata:
Categories:	FOV
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Licences

License:	CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	27.08.2024

Secondary language

Language:	English
Title:	Business data security in the implementation of chatgpt enterprise
Abstract:	The aim of the thesis was to investigate the implementation and use of generative models, especially generative pre-trained transformer (GPT) models, in the business environment of Company X and to understand their impact on business processes. With a focus on security and productivity, we examined the benefits and challenges of integrating these technologies and identified key findings that include improved efficiency, innovation, quality of service and data security. Methods used include case study, project manager interviews, data analysis and literature review. The main conclusions include an emphasis on the need to implement security protocols, to consider ethical aspects and to implement best practices in the implementation of generative models. Recommendations include the use of robust security mechanisms, optimization of business processes, and further exploration of the possibility of using generative models in a business environment.
Keywords:	generative models, GPT, business environment, security, productivity

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