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Anali Ekonomskog fakulteta u Subotici
2022, br. 48, str. 101-118
Analitika velike količine podataka kao menadžment alat - pregled stanja, trendovi i izazovi
Mašić Branislava, Dželetović Milenkob, Nešić Sandrac ORCID
aUniverzitet u Istočnom Sarajevu, Ekonomski fakultet - Pale, Republika Srpska, BiH
bUniverzitet u Beogradu, Fakultet bezbednosti, Srbija
cUniverzitet Singidunum, Fakultet za medije i komunikacije - FMK, Beograd, Srbija

e-adresa: masicbranislav@gmail.com, milenkodz@telekom.rs, sandra.nesic@fmk.edu.rs
Ključne reči: "Veliki" podaci; analitika velike količine podataka; tehnološke promene; poslovne performanse; konkurentska prednost
Sažetak
Inovativne digitalne tehnologije i stalno promenljivo poslovno okruženje su transformisali, i tek će transformisati, kompanije i privredne grane širom sveta. Imajući u vidu predstojeća tehnološka dostignuća, i razvoj analitike velike količine podataka (engl. big data analytics), algoritama mašinskog učenja (engl. machine learning algorithms), rešenja u okviru računarstva u oblaku (engl. cloud computing), veštačke inteligencije (engl. artificial intelligence), interneta stvari (engl. internet of things), ova transformacija će postati još očiglednija. Budući da živimo u svetu koji je sve više orijentisan, odnosno koji se sve više oslanja na podatke (engl. data-driven), tehnologije unose promene kako u poslovne i aktivnosti vezane za posao, tako i u aktivnosti i interakcije koje obavljamo svakodnevno. Ovaj rad je usredsređen na "velike" podatke (engl. big data) i na analitiku velike količine podataka čije usvajanje, posmatrano sa stanovništva organizacija, može doprineti poboljšanju poslovnih performansi i konkurentnosti. Cilj rada je da, na osnovu pregleda odabrane literature i istraživanja, ispita u kojoj meri je analitika velike količine podataka zastupljena u kompanijama, kao i da naglasi važnu ulogu koju analitika velike količine podataka može igrati u postizanju boljih poslovnih rezultata. Pored toga, sažeto su predstavljeni važniji izazovi i poteškoće koji se javljaju prilikom usvajanja programa analitike velike količine podataka u kompanijama.
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O članku

jezik rada: engleski
vrsta rada: izvorni naučni članak
DOI: 10.5937/AnEkSub2248101M
primljen: 03.02.2022.
prihvaćen: 04.10.2022.
objavljen u SCIndeksu: 17.12.2022.
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