Comparison of the E-LT vs ETL Method in Data Warehouse Implementation: A Qualitative Study

Edward Manopo Haryono, Fahmi, Adi Setiawan Tri W, Indra Gunawan, Achmad Nizar Hidayanto, Untung Rahardja

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Citations (Scopus)

Abstract

The data warehouse is an enterprise system that archives various kinds of data from various main systems and integrates them into a place. There are two data processing methods in implementing a data warehouse, namely ETL (Extract, Transform, Load) and E-LT (Extract, Load, Transform). In determining the implementation of a data warehouse, it is often difficult to choose the appropriate method. Because this is related to Cost, Process, Performance, and Continuous Improvement in a company. This paper discusses the implementation of a data warehouse in various industries by conducting a survey to compare the use of ETL and E-LT methods. The survey was conducted on people with backgrounds in work related to data warehouses from various industries. Based on the results of this survey, it is hoped that a better method of implementing a data warehouse can be obtained.

Original languageEnglish
Title of host publicationProceedings - 2nd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages115-120
Number of pages6
ISBN (Electronic)9781728191676
DOIs
Publication statusPublished - 19 Nov 2020
Event2nd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2020 - Virtual, Jakarta, Indonesia
Duration: 19 Nov 202020 Nov 2020

Publication series

NameProceedings - 2nd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2020

Conference

Conference2nd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2020
Country/TerritoryIndonesia
CityVirtual, Jakarta
Period19/11/2020/11/20

Keywords

  • data warehouse
  • E-LT
  • ETL

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