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research-article

Towards a maturity model for corporate data quality management

Authors:

Boris OttoAuthors Info & Claims

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

Pages 231 - 238

https://doi.org/10.1145/1529282.1529334

Published: 08 March 2009 Publication History

Abstract

High-quality corporate data is a prerequisite for world-wide business process harmonization, global spend analysis, integrated service management, and compliance with regulatory and legal requirements. Corporate Data Quality Management (CDQM) describes the quality oriented organization and control of a company's key data assets such as material, customer, and vendor data. With regard to the aforementioned business drivers, companies demand an instrument to assess the progress and performance of their CDQM initiative. This paper proposes a reference model for CDQM maturity assessment. The model is intended to be used for supporting the build process of CDQM. A case study shows how the model has been successfully implemented in a real-world scenario.

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Cited By

Hunziker SBlankenagel MHunziker SBlankenagel M(2024)AktionsforschungsdesignForschungsdesign im Bereich Betriebswirtschaft und Management10.1007/978-3-658-44859-2_7(133-158)Online publication date: 11-Jul-2024
https://doi.org/10.1007/978-3-658-44859-2_7
Hunziker SBlankenagel MHunziker SBlankenagel M(2024)Action Research DesignResearch Design in Business and Management10.1007/978-3-658-42739-9_7(117-139)Online publication date: 4-Jan-2024
https://doi.org/10.1007/978-3-658-42739-9_7
Mayer JLanzerath MWutzler JQuick RPeruscha M(2024)How to Unlock the Value of Your Data: Six Design Guidelines for Implementing Data StrategiesTechnologies for Digital Transformation10.1007/978-3-031-52120-1_14(239-255)Online publication date: 29-May-2024
https://doi.org/10.1007/978-3-031-52120-1_14
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Index Terms

Towards a maturity model for corporate data quality management
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. System management
        Technology audits

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Published In

cover image ACM Conferences

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

March 2009

2347 pages

ISBN:9781605581668

DOI:10.1145/1529282

Conference Chairs:
Sung Y. Shin
South Dakota State University, United States
,
Sascha Ossowski
University Rey Juan Carlos, Spain

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 March 2009

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March 8, 2009 - March 12, 2008

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Cited By

Hunziker SBlankenagel MHunziker SBlankenagel M(2024)AktionsforschungsdesignForschungsdesign im Bereich Betriebswirtschaft und Management10.1007/978-3-658-44859-2_7(133-158)Online publication date: 11-Jul-2024
https://doi.org/10.1007/978-3-658-44859-2_7
Hunziker SBlankenagel MHunziker SBlankenagel M(2024)Action Research DesignResearch Design in Business and Management10.1007/978-3-658-42739-9_7(117-139)Online publication date: 4-Jan-2024
https://doi.org/10.1007/978-3-658-42739-9_7
Mayer JLanzerath MWutzler JQuick RPeruscha M(2024)How to Unlock the Value of Your Data: Six Design Guidelines for Implementing Data StrategiesTechnologies for Digital Transformation10.1007/978-3-031-52120-1_14(239-255)Online publication date: 29-May-2024
https://doi.org/10.1007/978-3-031-52120-1_14
M ABosch JOlsson H(2023)Maturity Assessment Model for Industrial Data Pipelines2023 30th Asia-Pacific Software Engineering Conference (APSEC)10.1109/APSEC60848.2023.00062(503-513)Online publication date: 4-Dec-2023
https://doi.org/10.1109/APSEC60848.2023.00062
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von Leipzig Tdu Toit JOrtmann F(2023)Driving Big Data Capabilities and Sustainable Innovation in OrganisationsSmart, Sustainable Manufacturing in an Ever-Changing World10.1007/978-3-031-15602-1_56(779-795)Online publication date: 4-Mar-2023
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Gökalp MGökalp EGökalp SKoçyiğit A(2023)The development of data analytics maturity assessment frameworkJournal of Software: Evolution and Process10.1002/smr.241535:8Online publication date: 7-Aug-2023
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Yang K(2023)Data QualityQuality in the Era of Industry 4.010.1002/9781119932475.ch6(199-236)Online publication date: 8-Dec-2023
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Nulhusna RTaufiq NRuldeviyani Y(2022)Strategy to Improve Data Quality Management: A Case Study of Master Data at Government Organization in Indonesia2022 International Symposium on Information Technology and Digital Innovation (ISITDI)10.1109/ISITDI55734.2022.9944466(150-155)Online publication date: 27-Jul-2022
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