Without Data Quality, There Is No Data Migration
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 i...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-05-01
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| Series: | Big Data and Cognitive Computing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-2289/5/2/24 |
| _version_ | 1827692260756553728 |
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| author | Otmane Azeroual Meena Jha |
| author_facet | Otmane Azeroual Meena Jha |
| author_sort | Otmane Azeroual |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T11:18:49Z |
| format | Article |
| id | doaj.art-2536fd97c6a54d04922313b5d7c782c0 |
| institution | Directory Open Access Journal |
| issn | 2504-2289 |
| language | English |
| last_indexed | 2024-03-10T11:18:49Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj.art-2536fd97c6a54d04922313b5d7c782c02023-11-21T20:11:54ZengMDPI AGBig Data and Cognitive Computing2504-22892021-05-01522410.3390/bdcc5020024Without Data Quality, There Is No Data MigrationOtmane Azeroual0Meena Jha1German Center for Higher Education Research and Science Studies (DZHW), 10117 Berlin, GermanyCentre for Intelligent Systems, School of Engineering and Technology, College of Information and Communication Technology (ICT), Central Queensland University, Sydney, NSW 2000, AustraliaData 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.https://www.mdpi.com/2504-2289/5/2/24data qualitycleansingdata migrationdependencystructural equation models (SEM)business enterprise success |
| spellingShingle | Otmane Azeroual Meena Jha Without Data Quality, There Is No Data Migration Big Data and Cognitive Computing data quality cleansing data migration dependency structural equation models (SEM) business enterprise success |
| title | Without Data Quality, There Is No Data Migration |
| title_full | Without Data Quality, There Is No Data Migration |
| title_fullStr | Without Data Quality, There Is No Data Migration |
| title_full_unstemmed | Without Data Quality, There Is No Data Migration |
| title_short | Without Data Quality, There Is No Data Migration |
| title_sort | without data quality there is no data migration |
| topic | data quality cleansing data migration dependency structural equation models (SEM) business enterprise success |
| url | https://www.mdpi.com/2504-2289/5/2/24 |
| work_keys_str_mv | AT otmaneazeroual withoutdataqualitythereisnodatamigration AT meenajha withoutdataqualitythereisnodatamigration |