The value of good data - A quality perspective a framework for discussion

Tony O'Brien; Arun Sukumar; Markus Helfert

The value of good data - A quality perspective a framework for discussion

Tony O'Brien, Arun Sukumar, Markus Helfert

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Abstract

This study has highlighted the benefits and value of quality information and the direct consequences associated with low quality data. This paper also describes a number of taxonomies which may be used to classify costs relating to both the consequences of low quality data and the costs of improving and assuring on-going data quality. The study then provides practical examples of data quality improvement initiatives undertaken within two large organisations. Finally a data governance model is proposed centring on three inter-related fundamental elements namely: People, Processes and Data, where any attempt to improve the quality of data within any organisation must be focussed around these three essential elements.

Original language	English
Title of host publication	ICEIS 2013 - Proceedings of the 15th International Conference on Enterprise Information Systems
Pages	555-562
Number of pages	8
Volume	2
Publication status	Published - 2013
Externally published	Yes
Event	15th International Conference on Enterprise Information Systems, ICEIS 2013 - Angers, France Duration: 4 Jul 2013 → 7 Jul 2013

Conference

Conference	15th International Conference on Enterprise Information Systems, ICEIS 2013
Country/Territory	France
City	Angers
Period	4/07/13 → 7/07/13

Keywords

Cost benefits
Data assurance
Data quality
Information value management
It governance
It management

ASJC Scopus subject areas

Information Systems
Information Systems and Management

Cite this

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title = "The value of good data - A quality perspective a framework for discussion",

abstract = "This study has highlighted the benefits and value of quality information and the direct consequences associated with low quality data. This paper also describes a number of taxonomies which may be used to classify costs relating to both the consequences of low quality data and the costs of improving and assuring on-going data quality. The study then provides practical examples of data quality improvement initiatives undertaken within two large organisations. Finally a data governance model is proposed centring on three inter-related fundamental elements namely: People, Processes and Data, where any attempt to improve the quality of data within any organisation must be focussed around these three essential elements.",

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AU - Sukumar, Arun

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AB - This study has highlighted the benefits and value of quality information and the direct consequences associated with low quality data. This paper also describes a number of taxonomies which may be used to classify costs relating to both the consequences of low quality data and the costs of improving and assuring on-going data quality. The study then provides practical examples of data quality improvement initiatives undertaken within two large organisations. Finally a data governance model is proposed centring on three inter-related fundamental elements namely: People, Processes and Data, where any attempt to improve the quality of data within any organisation must be focussed around these three essential elements.

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KW - Data assurance

KW - Data quality

KW - Information value management

KW - It governance

KW - It management

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M3 - Conference proceeding

AN - SCOPUS:84887633046

SN - 9789898565600

VL - 2

SP - 555

EP - 562

BT - ICEIS 2013 - Proceedings of the 15th International Conference on Enterprise Information Systems

T2 - 15th International Conference on Enterprise Information Systems, ICEIS 2013

Y2 - 4 July 2013 through 7 July 2013

ER -

The value of good data - A quality perspective a framework for discussion

Abstract

Conference

Keywords

ASJC Scopus subject areas

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Cite this