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DESCRIPTION:Click for Latest Location Information: http://edw2022.dataversi
 ty.net/sessionPop.cfm?confid=129&proposalid=13317\nSemantic transformation 
 for data in motion has been a continuous problem for enterprises since the 
 need arose to share data between applications, and various approaches have 
 been proposed to solve it. This presentation proposes a new architectu
 re to handle semantic data transformations by using graph databases combine
 d with a set of microservices. The solution presents microservices in the f
 orm of transformation patterns that traverse the graphs to find the right r
 esults. The proposed architecture provides a new level of agility, does not
  require any modifications to either the data source or target, and can be 
 seamlessly integrated into existing transformation infrastructures. By impl
 ementing data lineage it is possible with AI algorithms to predict sem
 antic values and therefore significantly reduce labor-intensive data refere
 nce processes. 
DTSTART:20220324T083000
SUMMARY:Semantic Data Transformation Utilizing Graphs and Micro Services
DTEND:20220324T092959
LOCATION: See Description
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