Learning-based Assistant for Data Migration of Enterprise Information Systems

Data migration from source to target information system is a critical step for modernizing information systems. Central to data migration is data transform that transforms the source system data into target system. In this paper we present a tool that assists the experts in creating the data transfo...

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Vydáno v:IEEE/ACM International Conference on Automated Software Engineering : [proceedings] s. 1121 - 1125
Hlavní autoři: Mitra, Sayandeep, Mukherjee, Debayan, Bandyopadhyay, Atreya, Chowdhury, Rajdip, Medicherla, Raveendra Kumar, Bhattacharya, Indrajit, Naik, Ravindra
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.11.2021
Témata:
Data Migration
Data models
Data Transformation
Enterprise Information System
Generators
Information systems
Knowledge representation
Machine learning
Program Synthesis
Programming by Examples(PBE)
Software engineering
Transforms
ISSN:2643-1572
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Shrnutí:Data migration from source to target information system is a critical step for modernizing information systems. Central to data migration is data transform that transforms the source system data into target system. In this paper we present a tool that assists the experts in creating the data transformation specification by (a) suggesting candidate field matches between the source and target data models using machine learning and knowledge representation, and (b) rules for the data transformation using program synthesis. It takes the expert's feedback for the identified matches and synthesized rules and proposes new matches and transformation rules. We have executed our tool on real-life industrial data. Our schema matching recall at 5 is 0.76, while for the rule generator recall at 2 is 0.81.
ISSN:2643-1572
DOI:10.1109/ASE51524.2021.9678533