Rancang Bangun Real-Time Business Intelligence Untuk Subjek Kegiatan Akademik pada Universitas Menggunakan Change Data Capture

Abstract

Abstract. The running of academic activities in university continuously adds more data to the existing operational system. The data are not ready for the university strategic decision making, preparing reports for accreditation purposes and academic units. Real-time business intelligence application using data warehouse can become a solution for data analysis. The process of creating a data warehouse includes designing data warehouse, retrieving academic data from multiple data sources, extracting, transforming, loading (ETL) process, creating cube; and generating report. ETL processes are conducted by using a Pull Change Data Capture approach so that data changes during a certain period can be transferred in real-time. The higher the frequency of data change requests brings us closer to real-time and requires less time than loading all the data.Keywords: real-time, business intelligence, data warehouse, academic, change data capture Abstrak.  Kegiatan akademik di universitas berjalan terus menerus dan semakin menambah banyak data pada sistem operasional yang sudah ada. Data tersebut masih belum dapat dimanfaatkan oleh pihak universitas dalam pengambilan keputusan strategis, pembuatan laporan untuk keperluan akreditasi dan unit-unit akademik. Aplikasi real-time business intelligence menggunakan data warehouse menjadi solusi untuk analisa data. Proses pembuatan data warehouse meliputi perancangan data warehouse; pengambilan data akademik dari sumber data; proses extraction, transformation, loading (ETL); pembuatan cube; dan pembuatan laporan. Proses ETL dilakukan menggunakan pendekatan Change Data Capture Pull agar perubahan data selama periode tertentu dapat dipindahkan secara real-time. Semakin tinggi frekuensi permintaan perubahan data akan semakin mendekati real-time dan semakin membutuhkan waktu yang singkat dibandingkan dengan me-load semua data.Kata Kunci: real-time, business intelligence, data warehouse, akademik, change data capture