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.identifier.uri |
https://scholarsbank.uoregon.edu/xmlui/handle/1794/24786 |
|
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.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 |