Root Cause Analysis and Remediation for Quality and Value Improvement in Machine Learning Driven Information Models

Shelernaz Azimi, Claus Pahl

Abstract

Data quality is an important factor that determines the value of information in organisations. Information creates financial value, but depends largely on the quality of the underlying data. Today, data is more and more processed using machine-learning techniques applied to data in order to convert raw source data into valuable information. Furthermore, data and information are not directly accessed by their users, but are provided in the form of ’as-a-service’ offerings. We introduce here a framework based on a number of quality factors for machine-learning generated information models. Our aim is to link back the quality of these machine-learned information models to the quality of the underlying source data. This would enable to (i) determine the cause of information quality deficiencies arising from machine-learned information models in the data space and (ii) allowing to rectify problems by proposing remedial actions at data level and increase the overall value. We will investigate this for data in the Internet-of-Things context.

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Paper Citation


in Harvard Style

Azimi S. and Pahl C. (2020). Root Cause Analysis and Remediation for Quality and Value Improvement in Machine Learning Driven Information Models.In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-423-7, pages 656-665. DOI: 10.5220/0009783106560665


in Bibtex Style

@conference{iceis20,
author={Shelernaz Azimi and Claus Pahl},
title={Root Cause Analysis and Remediation for Quality and Value Improvement in Machine Learning Driven Information Models},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2020},
pages={656-665},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009783106560665},
isbn={978-989-758-423-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Root Cause Analysis and Remediation for Quality and Value Improvement in Machine Learning Driven Information Models
SN - 978-989-758-423-7
AU - Azimi S.
AU - Pahl C.
PY - 2020
SP - 656
EP - 665
DO - 10.5220/0009783106560665