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Title:Podatkovna analitika v digitalnem marketingu
Authors:ID Zahariev, Martin (Author)
ID Marolt, Marjeta (Mentor) More about this mentor... New window
Files:.pdf VS_Zahariev_Martin_2026.pdf (3,35 MB)
MD5: 80AE161A66B5BACA585C956F135E7581
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FOV - Faculty of Organizational Sciences in Kranj
Abstract:Diplomsko delo obravnava razvoj podatkovno‑analitične rešitve za podporo odločanju v digitalnem marketingu z uporabo platforme Databricks. Osredotoča se na vzpostavitev celotnega procesa obdelave podatkov, ki vključuje generiranje sintetičnih, a realističnih podatkov s pomočjo Python skript, njihovo shranjevanje v formatu Parquet ter organizacijo v podatkovni model zvezdne sheme, kar zagotavlja strukturirano in učinkovito izvajanje analitičnih poizvedb. S sistemom Databricks Workflows je vzpostavljena avtomatizacija postopkov, ki omogoča ponovljivo, časovno načrtovano in zanesljivo izvajanje vseh faz obdelave, od generiranja do posodabljanja tabel v podatkovni bazi. Ključne analize so izvedene z Databricks SQL Editorjem. Rezultati so prikazani z vizualizacijami, ki omogočajo jasen vpogled v trende, razlike med segmenti uporabnikov ter ključne kazalnike porabe, kar prispeva k boljši interpretaciji vedenjskih vzorcev. Glavni cilj diplomskega dela je prikazati, kako lahko celovit, avtomatiziran in ponovljiv analitični proces izboljša zanesljivost vpogledov in skrajša čas do uporabne informacije ter tako predstavlja učinkovito osnovo za podatkovno podprto odločanje v digitalnem marketingu. Analitični proces se izkaže kot ponovljiv, časovno učinkovit in primeren za izvedbo analiz in vizualizacije vedenjskih vzorcev uporabnikov.
Keywords:analiza podatkov, Databricks, marketinška optimizacija, avtomatizacija podatkovnih procesov, SQL
Place of publishing:Kranj
Year of publishing:2026
PID:20.500.12556/DKUM-97594 New window
COBISS.SI-ID:286267907 New window
Publication date in DKUM:28.07.2026
Views:324
Downloads:8
Metadata:XML DC-XML DC-RDF
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:23.03.2026

Secondary language

Language:English
Title:Data analytics in digital marketing
Abstract:The thesis addresses the development of a data-analytics solution designed to support decision-making in digital marketing using the Databricks platform. It focuses on establishing a complete data processing pipeline that includes the generation of synthetic yet realistic data using Python scripts, their storage in Parquet format, and their organization within a star schema data model, which enables structured and efficient analytical querying. Automation of the entire workflow was implemented using Databricks Workflows, allowing repeatable, scheduled, and reliable execution of all data processing stages, from data generation to updating tables in the database. Key analyses were performed using the Databricks SQL Editor, and the results were presented through visualizations that provide a clear overview of trends, differences between user segments, and key consumption indicators, thereby supporting the interpretation of behavioral patterns. The main objective of the thesis was to demonstrate how a comprehensive, automated, and repeatable analytical process can improve the reliability of insights and reduce the time required to obtain actionable information, thus providing an effective foundation for data-driven decision-making in digital marketing. The analytical process proved to be repeatable, time-efficient, and suitable for conducting analyses and visualizing user behavioral patterns.
Keywords:data analysis, Databricks, marketing optimization, data process automation, SQL


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