Show simple item record

A Framework for Improving Data Quality in Data Warehouse: A Case Study

dc.contributor.authorAli, Taghrid Z
dc.contributor.authorAbdelaziz, Tawfig M
dc.contributor.authorMaatuk, Abdelsalam M
dc.contributor.authorElakeili, Salwa M
dc.date.accessioned2021-08-23T11:01:46Z
dc.date.available2021-08-23T11:01:46Z
dc.date.issued2021
dc.identifier.urihttp://repository.limu.edu.ly/handle/123456789/3251
dc.description.abstractNowadays, the development of data warehouses shows the importance of data quality in business success. Data warehouse projects fail for many reasons, one of which is the low quality of data. High-quality data achievement in data warehouses is a persistent challenge. Data cleaning aims at finding, correcting data errors and inconsistencies. This paper presents a general framework for the implementation of data cleaning according to the scientific principles followed in the data warehouse field, where the framework offers guidelines that define and facilitate the implementation of the data cleaning process to the enterprises interested in the data warehouse field. The research methodology used in this study is qualitative research, in which the data are collected through system analyst interviews. The study concluded that the low level of data quality is an obstacle to any progress in the implementation of modern technological projects, where data quality is a prerequisite for the success of its business, including the data warehouse.en_US
dc.language.isoenen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.titleA Framework for Improving Data Quality in Data Warehouse: A Case Studyen_US
dc.typeArticleen_US


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record

Attribution 3.0 United States
Except where otherwise noted, this item's license is described as Attribution 3.0 United States