Authors:
Hyeonsook Kim
1
;
Samia Oussena
1
;
Ying zhang
1
and
Tony Clark
2
Affiliations:
1
Thames Valley University, United Kingdom
;
2
Middlesex University, United Kingdom
Keyword(s):
Data Merging Meta-model, Data Integration, Model Driven Engineering, Model Driven Data Integration, Automatic Model Transformation, Automatic Program Code Generation.
Related
Ontology
Subjects/Areas/Topics:
Business Analytics
;
Communication and Software Technologies and Architectures
;
Cross-Feeding between Data and Software Engineering
;
Data Engineering
;
Data Exchange and Integration
;
Data Warehouses and Data Mining
;
e-Business
;
Enterprise Information Systems
;
Model-Driven Engineering
;
Software Engineering
;
Software Engineering Methods and Techniques
Abstract:
Data merging is an essential part of ETL (Extract-Transform-Load) processes to build a data warehouse system. To avoid rewheeling merging techniques, we propose a Data Merging Meta-model (DMM) and its transformation into executable program codes in the manner of model driven engineering. DMM allows defining relationships of different model entities and their merging types in conceptual level and our formalized transformation described using ATL (ATLAS Transformation Language) enables automatic generation of PL/SQL packages to execute data merging in commercial ETL tools. With this approach data warehouse engineers can be relieved from burden of repetitive complex script coding and pain of maintaining consistency of design and implementation.