Learning-based Assistant for Data Migration of Enterprise Information Systems
Abstract
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.
BibTeX
@inproceedings{Mitra-al:ASE21,
author = {Sayandeep Mitra and
Debayan Mukherjee and
Atreya Bandyopadhyay and
Rajdip Chowdhury and
Raveendra Kumar Medicherla and
Indrajit Bhattacharya and
Ravindra Naik},
title = {Learning-based Assistant for Data Migration of Enterprise Information Systems},
booktitle = {ASE},
pages = {1121--1125},
publisher = {{IEEE}},
year = {2021},
}