A Reference Model for Product Data Profiling in Retail ERP Systems

Rolf Krieger, Christian Schorr

Abstract

Due to the high volume of data and the increasing automation in retail, more and more companies are dealing with procedures to improve the quality of product data. A promising approach is the use of machine learning methods that support the user in master data management. The development of such procedures demands error-free training data. This means that product data must be cleaned and labelled which requires extensive data profiling. For typical retail company data bases with usually complex and convoluted structures this exploration step can take a huge and expensive amount of time. In order to speed up this process we present a reference model and best practices for the systematic and efficient profiling and exploration of product data.

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Paper Citation


in Harvard Style

Krieger R. and Schorr C. (2019). A Reference Model for Product Data Profiling in Retail ERP Systems.In Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-377-3, pages 317-324. DOI: 10.5220/0007953303170324


in Bibtex Style

@conference{data19,
author={Rolf Krieger and Christian Schorr},
title={A Reference Model for Product Data Profiling in Retail ERP Systems},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2019},
pages={317-324},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007953303170324},
isbn={978-989-758-377-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - A Reference Model for Product Data Profiling in Retail ERP Systems
SN - 978-989-758-377-3
AU - Krieger R.
AU - Schorr C.
PY - 2019
SP - 317
EP - 324
DO - 10.5220/0007953303170324