Best Practices in Using Semantic Transformation in Data Integration to Address Data Integrity Issues
| dc.contributor.author | Balijepalli, Saketh | |
| dc.date.accessioned | 2019-07-17T22:43:54Z | |
| dc.date.available | 2019-07-17T22:43:54Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Data integration is a digital technology used to combine data from multiple sources and provide users with a unified view of data assets (Chen, Hu, & Xu, 2015; Davidovski, 2018). Data is typically loaded into a data warehouse via Execute-Transform-Load (ETL) operations (Hose et al. 2015); sometimes the transformed data lacks data integrity. This paper explores best practices in using semantic transformation to address data integrity issues caused by data integration. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1794/24786 | |
| dc.language.iso | en | en_US |
| dc.publisher | University of Oregon | en_US |
| dc.relation.ispartofseries | AIM Capstone;Balijepalli2019 | |
| dc.rights | Creative Commons BY-NC-ND 4.0-US | en_US |
| dc.subject | Data integration | en_US |
| dc.subject | ETL | en_US |
| dc.subject | Syntactic transformation | en_US |
| dc.subject | Semantic transformation | en_US |
| dc.subject | Business intelligence | en_US |
| dc.subject | Data analytics | en_US |
| dc.subject | Semantic ETL | en_US |
| dc.subject | Data warehouse | en_US |
| dc.subject | Semantic information | en_US |
| dc.subject | Data integrity | en_US |
| dc.title | Best Practices in Using Semantic Transformation in Data Integration to Address Data Integrity Issues | en_US |
| dc.type | Terminal Project | en_US |