A Data Warehouse System for an Analysis of Unemployment Rate in the Republic of Serbia

Abstract

In the paper, we present a data warehouse system to analyze the unemployment rate in the Republic of Serbia. The goal of our research is to improve the analytical capabilities of the unemployment rate in Serbia by creating a new business intelligence tool and predictive machine learning models. First, we discuss research motives and the unemployment problem, and then we present the development process of the proposed data warehouse system. The Data Warehouse Quality methodology has been deployed to assess the quality of the data. Machine learning algorithms have been utilized to build predictive models and gain insights into the differences in unemployment rates between young and experienced workers. Finally, we have created several reports to visually present the results of the proposed data analyses.

U radu predstavljamo sistem skladišta podataka za analizu stope nezaposlenosti u Republici Srbiji. Cilj našeg istraživanja je da unapredimo analitičke mogućnosti stope nezaposlenosti u Srbiji kreiranjem novog alata poslovne inteligencije i prediktivnih modela mašinskog učenja. Prvo razmatramo motive istraživanja i problem nezaposlenosti, a zatim predstavljamo proces razvoja predloženog sistema skladišta podataka. Metodologija kvaliteta skladišta podataka je primenjena za procenu kvaliteta podataka. Algoritmi mašinskog učenja su korišćeni za izgradnju prediktivnih modela i sticanje uvida u razlike u stopama nezaposlenosti između mladih i iskusnih radnika. Konačno, napravili smo nekoliko izveštaja kako bismo vizuelno predstavili rezultate predloženih analiza podataka.