master's thesis
Mark Žohar (Author), Peter Kokol (Mentor), Mary Alejandra Luiz Barreto (Co-mentor)

Abstract

In the fast-paced business landscape, unexpected events can pose significant challenges for companies. A lot of times, business intelligence presents a solution for companies in dealing with changes and improving organizational efficiency. As part of this master’s thesis, we have developed a business intelligence system that assists in the planning of new releases of smartphone components. We have simulated data and created reports, which can help the stakeholders to plan and analyze important milestones easily. We have tested two different data structures and showed how star schema is the most beneficial data structure for our BI system. We achieved this by restructuring data into a star schema model at different stages of migration and then compared the size of data and responsiveness of operations.

Keywords

business intelligence;star schema;data modeling;

Data

Language: English
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher: [M. Žohar]
UDC: 004.434:004.8(043.2)
COBISS: 158063363 Link will open in a new window
Views: 62
Downloads: 7
Average score: 0 (0 votes)
Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: Slovenian
Secondary title: Razvoj in optimizacija sistema poslovne inteligence
Secondary abstract: V hitro spreminjajočem se poslovnem okolju lahko nepričakovani dogodki predstavljajo velike izzive za podjetja. Pogosto lahko rešitev za izboljšanje organizacijske učinkovitosti in prilagajanja spremembam nudi uporaba poslovne inteligence. V okviru te magistrske naloge smo zato razvili sistem poslovne inteligence, ki pomaga pri načrtovanju novih izdaj komponent za pametne telefone. Simulirali smo podatke ter iz njih ustvarili poročila, ki lahko deležnikom pomagajo pri planiranju in analizi pomembnih mejnikov. Testirali smo dve podatkovni strukturi in prikazali, da je zvezdna shema najprimernejša za naš sistem poslovne inteligence. To smo dosegli z restrukturiranjem podatkov v model zvezdne sheme v različnih fazah migracije in nato primerjali velikost podatkov ter odzivnost operacij
Secondary keywords: poslovna inteligenca;zvezdna shema;podatkovno modeliranje;magistrske naloge;
Type (COBISS): Master's thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Informatika in tehnologije komuniciranja
Pages: 1 spletni vir (1 datoteka PDF (XVI, 68 f.))
ID: 19178409