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master's thesis
DISTRIBUIRANO PROCESIRANJE VELIKIH PODATAKA U POSLOVNIM PROCESIMA
Diplomski rad
Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, 2021. urn:nbn:hr:145:311460
Krizmanić, Gordana
Josip Juraj Strossmayer University of Osijek
Faculty of Economics in Osijek
Chair of Quantitative Methods and Informatics

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Krizmanić, G. (2021). DISTRIBUIRANO PROCESIRANJE VELIKIH PODATAKA U POSLOVNIM PROCESIMA : Diplomski rad (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:145:311460

Krizmanić, Gordana. "DISTRIBUIRANO PROCESIRANJE VELIKIH PODATAKA U POSLOVNIM PROCESIMA : Diplomski rad." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, 2021. https://urn.nsk.hr/urn:nbn:hr:145:311460

Krizmanić, Gordana. "DISTRIBUIRANO PROCESIRANJE VELIKIH PODATAKA U POSLOVNIM PROCESIMA : Diplomski rad." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, 2021. https://urn.nsk.hr/urn:nbn:hr:145:311460

Krizmanić, G. (2021). 'DISTRIBUIRANO PROCESIRANJE VELIKIH PODATAKA U POSLOVNIM PROCESIMA : Diplomski rad', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, accessed 03 October 2023, https://urn.nsk.hr/urn:nbn:hr:145:311460

Krizmanić G. DISTRIBUIRANO PROCESIRANJE VELIKIH PODATAKA U POSLOVNIM PROCESIMA : Diplomski rad [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek; 2021 [cited 2023 October 03] Available at: https://urn.nsk.hr/urn:nbn:hr:145:311460

G. Krizmanić, "DISTRIBUIRANO PROCESIRANJE VELIKIH PODATAKA U POSLOVNIM PROCESIMA : Diplomski rad", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, Osijek, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:145:311460

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Metadata
TitleDISTRIBUIRANO PROCESIRANJE VELIKIH PODATAKA U POSLOVNIM PROCESIMA : Diplomski rad
Title (english)DISTRIBUTED BIG DATA PROCESSING IN BUSINESS PROCESSES : Graduate paper
AuthorGordana Krizmanić
MentorSlobodan Jelić (mentor)
Committee memberJosip Mesarić (predsjednik povjerenstva)
Committee memberSlobodan Jelić (član povjerenstva)
Committee memberMartina Briš Alić (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Economics in Osijek
(Chair of Quantitative Methods and Informatics)
Osijek
Defense date and country2021-09-30, Croatia
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Economics
Business Informatics
Abstract
U ovom diplomskom radu analizirat će se veliki podaci, te distribuirano procesiranje velikih podataka, a fokus će se staviti na utjecaj velikih podataka u poslovnim procesima. Ljudi svakodnevno generiraju ogromnu količinu raznorodnih podataka na temelju kojih se može doći do skrivenih informacija. Te skrivene informacije predstavljaju znanje na temelju kojih kompanije mogu donositi bolje poslovne odluke i unaprijediti svoje poslovanje, države mogu spriječiti različite vanjske ili unutarnje napade, dok u medicini mogu spasiti ljudske živote. Nakon što se podaci prikupe potrebno ih je prebaciti u upotrebljiv oblik, odnosno potrebno ih je procesirati kako bi se nad njima mogle vršiti različite analize. Apache Hadoop je alat otvorenog koda koji se koristi za spremanje, procesiranje i analizu velikih podataka. Stoga, u prvom dijelu ovog diplomskog rada fokus je stavljen na definiranje znanosti o podacima, velikim podacima, te alata Apache Hadoop i MapReduce tehnike procesiranja i njihovih mogućnosti. U drugom dijelu rada će se na praktičnom primjeru pokazati kako se veliki podaci procesiraju pomoću alata Apache Hadoop i MapReduce tehnike procesiranja. Zaključak donosi osvrt na procesiranje velikih podataka, kako se veliki podaci mogu pretvoriti u znanje pomoću alata za distribuirano procesiranje i omogućiti kompanijama da poboljšaju svoje poslovne procese, te što se očekuje u budućnosti kada su u pitanju veliki podaci i poslovni procesi.
Abstract (english)
In this graduate paper, big data and distributed big data processing will be analyzed, and the focus will be on the impact of big data in business processes. People generate a huge amount of diverse data daily based on which hidden information can be obtained. This hidden information represents the knowledge based on which companies can make better business decisions and improve their business, states can prevent various external or internal attacks, while in medicine they can save lives. After the data is collected, it is necessary to transfer it toa usable form, ie it is necessary to process it so that various analyzes can be performed on it. Apache Hadoop is an open-source tool used to store, process, and analyze big data. Therefore, in the first part of this paper, the focus is on defining the data science, big data, and the Apache Hadoop tool and MapReduce processing techniques and their capabilities. The second part of the paper will show a practical example of how large data is processed using the Apache Hadoop tool and MapReduce processing technique. The conclusion looks at big data processing, how big data can be turned into knowledge using distributed processing tools and enable companies to improve their business processes, and what is expected in the future when it comes to big data and business processes.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:145:311460
Study programmeTitle: Business economy; specializations in: Trade and logistics, Management, Logistic management , Business informatics
Course: Business informatics
Study programme type: university
Study level: graduate
Academic / professional title: Magistar/magistra ekonomije (Magistar/magistra ekonomije)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
RepositoryEFOS REPOSITORY
Created on2022-05-10 12:29:08