Without Data Quality, There Is No Data Migration

被引:9
作者
Azeroual, Otmane [1 ]
Jha, Meena [2 ]
机构
[1] German Ctr Higher Educ Res & Sci Studies DZHW, D-10117 Berlin, Germany
[2] Cent Queensland Univ, Coll Informat & Commun Technol ICT, Sch Engn & Technol, Ctr Intelligent Syst, Sydney, NSW 2000, Australia
关键词
data quality; cleansing; data migration; dependency; structural equation models (SEM); business enterprise success;
D O I
10.3390/bdcc5020024
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Data migration is required to run data-intensive applications. Legacy data storage systems are not capable of accommodating the changing nature of data. In many companies, data migration projects fail because their importance and complexity are not taken seriously enough. Data migration strategies include storage migration, database migration, application migration, and business process migration. Regardless of which migration strategy a company chooses, there should always be a stronger focus on data cleansing. On the one hand, complete, correct, and clean data not only reduce the cost, complexity, and risk of the changeover, it also means a good basis for quick and strategic company decisions and is therefore an essential basis for today's dynamic business processes. Data quality is an important issue for companies looking for data migration these days and should not be overlooked. In order to determine the relationship between data quality and data migration, an empirical study with 25 large German and Swiss companies was carried out to find out the importance of data quality in companies for data migration. In this paper, we present our findings regarding how data quality plays an important role in a data migration plans and must not be ignored. Without acceptable data quality, data migration is impossible.
引用
收藏
页数:12
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