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

2014 ◽  
Vol 5 (2) ◽  
Author(s):  
Stephanie Pamela Adithama
Keyword(s):  
Real Time ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Data Capture ◽  
Strategic Decision ◽  
Change Data Capture ◽  
Multiple Data ◽  
Academic Activities ◽  
Using Data ◽  
Unit Unit

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

scholarly journals Kajian Pendekatan Binary Log dalam Change Data Capture

2017 ◽  
pp. 11
Author(s):  
Muhammad Febrian Rachmadhan Amri ◽  
I Made Sukarsa ◽  
I Ketut Adi Purnawan
Keyword(s):  
Data Management ◽  
Real Time ◽  
Data Warehouse ◽  
Data Capture ◽  
Problem Solution ◽  
Time Data ◽  
Quality Of Data ◽  
Data Manipulation ◽  
Change Data Capture ◽  
Real Time Data

The online business era causes the form of transactions to occur so quickly that the information stored in the data warehouse becomes invalid. Companies are required to have a strong system, which is a system that is real time in order to be able to perform data loading into the media repository that resides on different hosts in the near-real time. Data Warehouse is used as a media repository of data that has the nature of subject-oriented, integrated, time-variant, and is fixed. Data Warehouse can be built into real time management with the advantages possessed and utilize Change Data Capture. Change Data Capture (CDC) is a technique that can be used as problem solution to build real time data warehousing (RTDW). The binary log approach in change data capture is made to record any data manipulation activity that occurs at the OLTP level and is managed back before being stored into the Data Warehouse (loading process). This can improve the quality of data management so that the creation of the right information, because the information available is always updated. Testing shows that Binary Log approach in Change Data Capture (BinlogCDC) is able to generate real time data management, valid current information, dynamic communication between systems, and data management without losing any information from data manipulation.

scholarly journals Change Data Capture on OLTP Staging Area for Nearly Real Time Data Warehouse Base on Database Trigger

2012 ◽  
Vol 52 (11) ◽  
pp. 32-37
Author(s):  
I MadeSukarsa ◽  
Ni Wayan Wisswani ◽  
I K. Gd. Darma Putra ◽  
Linawati Linawati
Keyword(s):  
Real Time ◽  
Data Warehouse ◽  
Data Capture ◽  
Time Data ◽  
Change Data Capture ◽  
Staging Area ◽  
Real Time Data

scholarly journals Mapping Student Data Using Data Warehouse for Promotion at Vocational High School of Z

2020 ◽  
Vol 3 (2) ◽  
pp. 55
Author(s):  
Khoirudin Eko Nurcahyo ◽  
Sucipto Sucipto ◽  
Arie Nugroho
Keyword(s):  
High School ◽  
Data Warehouse ◽  
Junior High School ◽  
Business Intelligence ◽  
Junior High ◽  
Vocational High School ◽  
Dimensional Modeling ◽  
Education Organization ◽  
Using Data ◽  
Analyze Data

<em>The purpose of this study is provide data warehouse modeling which make executive of school can analyze data easily, the problem is executive of school are analysis list registrant list difficulty, what the most and least registrant junior high school come from and the major which most and least registrant. This study do is because how important data management on education organization and how the data can be managed better. The study use descriptive quantitative method research and use 4 step data warehouse dimensional modeling by Kimball. On building data warehouse used ETL, data be extracted and transformed into data warehouse as dimension and fact. For next data be imported and be showed by web base business intelligence app. The result of this study is an web base business intelligence app which can show sum of registrant on gender, majors, junior high school graduate come from, recommendation and register year. Data warehouse is good at data analyzing for decision making, because data warehouse can show information quickly and accurate.</em>

Real-time high-level video understanding using data warehouse

2006 ◽  
Author(s):  
Bruno Lienard ◽  
Xavier Desurmont ◽  
Bertrand Barrie ◽  
Jean-Francois Delaigle
Keyword(s):  
Real Time ◽  
Data Warehouse ◽  
Video Understanding ◽  
Using Data ◽  
High Level
Sign in / Sign up

Export Citation Format

Share Document