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Muhammad Hilman
Uinversitas Islam Syekh Yusuf
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Analisis Faktor Optimalisasi Proses Etl Pada Data Warehouse Sebagai Pendukung Pengambilan Keputusan Management Dengan Business Intelligence Muhammad Hilman; Djamaludin Djamaludin
Faktor Exacta Vol 11, No 1 (2018)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (509.786 KB) | DOI: 10.30998/faktorexacta.v11i1.2325

Abstract

Abstract. The company's need to make decisions appropriately and quickly on the basis of market facts is becoming more critical in order to survive. It is supported by Business Intelligence (BI) tactical in the company. The application of tactical BI as a support for tactical decision making requires some analysis of the current BI system such as data that becomes the material of decision-making must be current data and have a fast query process. The analysis used can be with ETL process and fast query process to support tactical decision making environment because ETL (Extract Transform Loading) in developing data warehouse process is a process that takes the longest time. The success of the ETL process is strongly influenced by the quality of existing data on OLTP databases. This research aims to find the optimization of ETL process with data warehouse development method. The research method used is the form of inductive study of ETL in data warehouse. The conclusion is that optimization techniques that have significant impacts can be used to implement Business Intelligence such as the application of parallel transformation, pipelining data, and dimensional data with bulk and parallel data load. For large amounts of data, then the results provided will also have greater impact and more optimal. By applying this optimization, it is expected to support faster query processing and more optimal ETL processes. Keywords: Business Intelligence, Data warehouse, ETL, Query, Optimalization
Co-Authors Djamaludin Djamaludin