Paper Info
Title
Applying Test-First and Parallel Processing Techniques to ERP Data Conversion
Abstract
Enterprise Resource Planning (ERP) systems provide a unified solution for streamlining the operations and flow of information across multiple divisions of an organization. Most of the functionality in ERP systems is master-data driven, and hence the migration of data from legacy systems to ERP is a very important activity during development. Such data must be correctly migrated so that integration and acceptance testing of specific functionalities can be performed. However, the high complexity of ERP systems, coupled with the large volume of data involved, make ERP data conversion an immense challenge for software practitioners. In this paper we tackle the ERP data conversion problem using a test-first approach. The approach seeks to identify and correct data mapping errors and anomalies prior to initiating the data conversion process. Fixing such errors early can avoid having failures occur during data conversion, thereby resulting in cost and time savings. In an effort to further reduce the length of time spent converting large volumes of data, we perform parallel execution of the data conversion program. We have conducted an industrial case study that applies our approach to two ERP projects with favorable results.
Year
DOI
Venue
2012
10.1109/ITNG.2012.46
Information Technology: New Generations
Keywords
Field
DocType
erp data conversion,erp system,data conversion program,data conversion,erp project,large volume,test-first approach,erp data conversion problem,correct data,data conversion process,legacy systems,failure analysis,organizations,data migration,testing,computational complexity,parallel processing,software maintenance,parallelization,electronic data interchange,acceptance testing,databases,information flow
Information flow (information theory),Enterprise resource planning,Software engineering,Electronic data interchange,Data mapping,Computer science,Data conversion,Software maintenance,Legacy system,Data migration
Conference
ISBN
Citations 
PageRank 
978-1-4673-0798-7
0
0.34
References 
Authors
5
3
Name
Order
Citations
PageRank
Talukdar S. Asgar100.34
Mohammed Akour254.81
Tariq M. King313116.61