改进数据质量管理的策略:以印度尼西亚政府组织主数据为例

Rizqa Nulhusna, Nur Fajar Taufiq, Y. Ruldeviyani
{"title":"改进数据质量管理的策略:以印度尼西亚政府组织主数据为例","authors":"Rizqa Nulhusna, Nur Fajar Taufiq, Y. Ruldeviyani","doi":"10.1109/ISITDI55734.2022.9944466","DOIUrl":null,"url":null,"abstract":"Data is important for organizations to support their operational and decisional activities. Organizations need to ensure that their data is high quality and appropriate for use. This study was conducted at a Government Organization in Indonesia that is currently focusing on a reform agenda in information technology and databases. The organization established a dedicated data management unit and executed data updating programs to support data quality management (DQM). The purpose of this study is to recommend the strategy to improve the organization's DQM, especially on master data. Therefore, it is important to assess the DQM Maturity Level to determine their current state and build up recommendations upon that. This study assessed the DQM maturity level on the organization's master data using the Data Quality Framework by D. Loshin. Overall, the maturity level of DQM on the organization's master data is at level 3 (defined). Recommendations for improving DQM in the organization based on DQM activities in DMBOK are adopting or developing a data quality framework to guide DQM strategy, managing data quality rules related to data quality dimensions, ensuring data quality publication, establishing data quality SLAs and developing dashboard and reporting applications for data users.","PeriodicalId":312644,"journal":{"name":"2022 International Symposium on Information Technology and Digital Innovation (ISITDI)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Strategy to Improve Data Quality Management: A Case Study of Master Data at Government Organization in Indonesia\",\"authors\":\"Rizqa Nulhusna, Nur Fajar Taufiq, Y. Ruldeviyani\",\"doi\":\"10.1109/ISITDI55734.2022.9944466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data is important for organizations to support their operational and decisional activities. Organizations need to ensure that their data is high quality and appropriate for use. This study was conducted at a Government Organization in Indonesia that is currently focusing on a reform agenda in information technology and databases. The organization established a dedicated data management unit and executed data updating programs to support data quality management (DQM). The purpose of this study is to recommend the strategy to improve the organization's DQM, especially on master data. Therefore, it is important to assess the DQM Maturity Level to determine their current state and build up recommendations upon that. This study assessed the DQM maturity level on the organization's master data using the Data Quality Framework by D. Loshin. Overall, the maturity level of DQM on the organization's master data is at level 3 (defined). Recommendations for improving DQM in the organization based on DQM activities in DMBOK are adopting or developing a data quality framework to guide DQM strategy, managing data quality rules related to data quality dimensions, ensuring data quality publication, establishing data quality SLAs and developing dashboard and reporting applications for data users.\",\"PeriodicalId\":312644,\"journal\":{\"name\":\"2022 International Symposium on Information Technology and Digital Innovation (ISITDI)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Symposium on Information Technology and Digital Innovation (ISITDI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISITDI55734.2022.9944466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Symposium on Information Technology and Digital Innovation (ISITDI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISITDI55734.2022.9944466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

数据对于支持组织的操作和决策活动非常重要。组织需要确保他们的数据是高质量的并且适合使用。这项研究是在印度尼西亚的一个政府组织进行的,该组织目前正侧重于信息技术和数据库的改革议程。该组织建立了一个专门的数据管理单位,并执行数据更新程序,以支持数据质量管理(DQM)。本研究的目的是推荐改进组织DQM的策略,特别是在主数据上。因此,评估DQM成熟度级别以确定它们的当前状态并在此基础上构建建议是非常重要的。本研究使用D. Loshin的数据质量框架评估了组织主数据的DQM成熟度水平。总体而言,组织主数据上的DQM的成熟度级别为3级(已定义)。基于DMBOK中的DQM活动,改进组织中的DQM的建议包括采用或开发数据质量框架来指导DQM策略、管理与数据质量维度相关的数据质量规则、确保数据质量发布、建立数据质量sla以及为数据用户开发仪表板和报告应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Strategy to Improve Data Quality Management: A Case Study of Master Data at Government Organization in Indonesia
Data is important for organizations to support their operational and decisional activities. Organizations need to ensure that their data is high quality and appropriate for use. This study was conducted at a Government Organization in Indonesia that is currently focusing on a reform agenda in information technology and databases. The organization established a dedicated data management unit and executed data updating programs to support data quality management (DQM). The purpose of this study is to recommend the strategy to improve the organization's DQM, especially on master data. Therefore, it is important to assess the DQM Maturity Level to determine their current state and build up recommendations upon that. This study assessed the DQM maturity level on the organization's master data using the Data Quality Framework by D. Loshin. Overall, the maturity level of DQM on the organization's master data is at level 3 (defined). Recommendations for improving DQM in the organization based on DQM activities in DMBOK are adopting or developing a data quality framework to guide DQM strategy, managing data quality rules related to data quality dimensions, ensuring data quality publication, establishing data quality SLAs and developing dashboard and reporting applications for data users.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An RFID-Based Battery-Less Vibration Monitoring System for Electrical Appliances Gender and Intent Classification From Finger Swiping Behaviours on Gesture Keyboards Using LSTM Comparison of Naïve Bayes, C4.5 and K-Nearest Neighbor for Covid-19 Data Classification Gamification Methods of Game-Based Learning Applications in Medical Competence: A Systematic Literature Review The Implementation of Business Intelligence on Visualisation of Transaction Data Analysis using Dashboard System Case Study: XYZ Convenience Store
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1