Design and Implementation of an ETL Pipeline for Prospective Student Data Analysis in Higher Education Admissions

The number of universities in Indonesia continues to grow. This condition certainly makes the flow of new student admissions increasingly competitive between universities, thus encouraging universities to do branding, show quality, and do the right positioning. Therefore, it is important for univers...

Full description

Saved in:
Bibliographic Details
Main Authors: Nina Setiyawati, Dwi Hosanna Bangkalang, Gilang Windu Asmara
Format: Article
Language:Indonesian
Published: Islamic University of Indragiri 2025-09-01
Series:Sistemasi: Jurnal Sistem Informasi
Subjects:
Online Access:https://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/5158
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849247266447032320
author Nina Setiyawati
Dwi Hosanna Bangkalang
Gilang Windu Asmara
author_facet Nina Setiyawati
Dwi Hosanna Bangkalang
Gilang Windu Asmara
author_sort Nina Setiyawati
collection DOAJ
description The number of universities in Indonesia continues to grow. This condition certainly makes the flow of new student admissions increasingly competitive between universities, thus encouraging universities to do branding, show quality, and do the right positioning. Therefore, it is important for universities to adopt a data-driven approach that can provide in-depth insights into prospective students and the effectiveness of marketing strategies. The purpose of this study is to design and build an ETL (Extract, Transform, Load) pipeline to collect, process, and analyze prospective student data as part of the business intelligence (BI) system to be built. The proposed ETL architecture design supports automated microservices-based data transformation in data cleaning, normalization, and integration. In addition, it can also be used as a solution to increase the scalability and flexibility of data mobilization in the BI system. This study introduces a novel approach by designing an ETL pipeline within a business intelligence framework aimed at enhancing university marketing efforts. Unlike prior research, which has primarily applied business intelligence tools to evaluate academic activities within learning management systems, this work shifts the focus to marketing analytics. Additionally, while existing studies on higher education marketing often center around digital marketing techniques and the marketing mix, this research fills a gap by proposing a technical infrastructure that supports data-driven marketing through automated ETL processes. The resulting ETL was tested using several methods, namely Source to Target Count Testing, Source to Target Data Testing, Duplicate Data Check Testing, and Data Transformation Testing. The results of each test are valid
format Article
id doaj-art-e2b4284a578f4a5e93939189761245af
institution Kabale University
issn 2302-8149
2540-9719
language Indonesian
publishDate 2025-09-01
publisher Islamic University of Indragiri
record_format Article
series Sistemasi: Jurnal Sistem Informasi
spelling doaj-art-e2b4284a578f4a5e93939189761245af2025-08-20T03:58:15ZindIslamic University of IndragiriSistemasi: Jurnal Sistem Informasi2302-81492540-97192025-09-011452125213210.32520/stmsi.v14i4.51581173Design and Implementation of an ETL Pipeline for Prospective Student Data Analysis in Higher Education AdmissionsNina Setiyawati0Dwi Hosanna Bangkalang1Gilang Windu Asmara2Satya Wacana Christian UniversitySatya Wacana Christian UniversityMarikh Prigel TechnologyThe number of universities in Indonesia continues to grow. This condition certainly makes the flow of new student admissions increasingly competitive between universities, thus encouraging universities to do branding, show quality, and do the right positioning. Therefore, it is important for universities to adopt a data-driven approach that can provide in-depth insights into prospective students and the effectiveness of marketing strategies. The purpose of this study is to design and build an ETL (Extract, Transform, Load) pipeline to collect, process, and analyze prospective student data as part of the business intelligence (BI) system to be built. The proposed ETL architecture design supports automated microservices-based data transformation in data cleaning, normalization, and integration. In addition, it can also be used as a solution to increase the scalability and flexibility of data mobilization in the BI system. This study introduces a novel approach by designing an ETL pipeline within a business intelligence framework aimed at enhancing university marketing efforts. Unlike prior research, which has primarily applied business intelligence tools to evaluate academic activities within learning management systems, this work shifts the focus to marketing analytics. Additionally, while existing studies on higher education marketing often center around digital marketing techniques and the marketing mix, this research fills a gap by proposing a technical infrastructure that supports data-driven marketing through automated ETL processes. The resulting ETL was tested using several methods, namely Source to Target Count Testing, Source to Target Data Testing, Duplicate Data Check Testing, and Data Transformation Testing. The results of each test are validhttps://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/5158data analysisprospective studentsbusiness intelligenceetl pipelinedata driven marketing
spellingShingle Nina Setiyawati
Dwi Hosanna Bangkalang
Gilang Windu Asmara
Design and Implementation of an ETL Pipeline for Prospective Student Data Analysis in Higher Education Admissions
Sistemasi: Jurnal Sistem Informasi
data analysis
prospective students
business intelligence
etl pipeline
data driven marketing
title Design and Implementation of an ETL Pipeline for Prospective Student Data Analysis in Higher Education Admissions
title_full Design and Implementation of an ETL Pipeline for Prospective Student Data Analysis in Higher Education Admissions
title_fullStr Design and Implementation of an ETL Pipeline for Prospective Student Data Analysis in Higher Education Admissions
title_full_unstemmed Design and Implementation of an ETL Pipeline for Prospective Student Data Analysis in Higher Education Admissions
title_short Design and Implementation of an ETL Pipeline for Prospective Student Data Analysis in Higher Education Admissions
title_sort design and implementation of an etl pipeline for prospective student data analysis in higher education admissions
topic data analysis
prospective students
business intelligence
etl pipeline
data driven marketing
url https://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/5158
work_keys_str_mv AT ninasetiyawati designandimplementationofanetlpipelineforprospectivestudentdataanalysisinhighereducationadmissions
AT dwihosannabangkalang designandimplementationofanetlpipelineforprospectivestudentdataanalysisinhighereducationadmissions
AT gilangwinduasmara designandimplementationofanetlpipelineforprospectivestudentdataanalysisinhighereducationadmissions