<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This article presents an ETL (Extract, Transform, Load) prototype called Valery as alternative approach to migration process which includes a compiler for dynamic generation of SQL queries. Its main features involve: SQL dynamic generation, set of configuration commands and environment for file uploading. The tests use the Northwind academic database and an individual environment. The model implementation uses flat files and SQL as query language. Finally, there is an analysis of the results obtained.</p></abstract>

This article presents an ETL (Extract, Transform, Load) prototype called Valery as alternative approach to migration process which includes a compiler for dynamic generation of SQL queries. Its main features involve: SQL dynamic generation, set of configuration commands and environment for file uploading. The tests use the Northwind academic database and an individual environment. The model implementation uses flat files and SQL as query language. Finally, there is an analysis of the results obtained.

Alternative Development for Data Migration Using Dynamic Query Generation

Engineering Faculty, Universidad Distrital Francisco José de Caldas, Colombia

Computer Science Department, University of Oviedo, Spain

Applied Computer Systems

This work is licensed under the Creative Commons Attribution 4.0 Public License.

{"article-title":"Alternative Development for Data Migration Using Dynamic Query Generation"}

This article presents an ETL (Extract, Transform, Load) prototype called Valery as alternative approach to migration process which includes a compiler for...

Alternative Development for Data Migration Using Dynamic Query Generation

Published Online: May 28, 2016

Page range: 25 - 29

DOI: https://doi.org/10.1515/acss-2016-0003

Keywords
Data migration, Data transformation, ETL, schema mapping

© 2016 Riga Technical University

This work is licensed under the Creative Commons Attribution 4.0 Public License.

Alternative Development for Data Migration Using Dynamic Query Generation

Published Online: May 28, 2016

Page range: 25 - 29

DOI: https://doi.org/10.1515/acss-2016-0003

KeywordsData migration, Data transformation, ETL, schema mapping

© 2016 Riga Technical University

This work is licensed under the Creative Commons Attribution 4.0 Public License.

Keywords
Data migration, Data transformation, ETL, schema mapping