CC Corporate Data Quality (CC CDQ)

Type
applied research project
Start Date
November 1, 2006
End Date
December 31, 2016
URI
Status
ongoing
Keywords
Corporate Data Quality
CDQ
Datenmanagement
Stammdatenmanagement
Datenmodellierung
überbetriebliches Datenmanagement
Datenarchitektur
Prozessarchitektur
Geschäftsarchitektur
Description
Zur Verbesserung der Konzerndatenqualität braucht es konkrete Lösungsansätze. Das Kompetenzzentrum Corporate Data Quality soll die Visibilität des Themas und das "Business Alignment" in Unternehmen stärken. Zu den Arbeitsergebnissen gehören Methoden und Referenzarchitekturen, die zur Umsetzung von Corporate Data Quality beitragen. Im Zentrum steht der Wissenstransfer des Stands der Forschung in die Unternehmen. Gemeinsam mit Praxispartnern werden Best Practices und Benchmarks entwickelt.

Weitere Informationen unter: http://cdq.iwi.unisg.ch/
Leader contributor(s)
Member contributor(s)
Partner(s)
ABB Ltd.
Astra Zeneca plc
Bayer HealthCare AG
Beiersdorf AG
DB Netze
Drägerwerk AG & Co. KGaA
Ericsson AB
Festo AG & Co. KG
Merck KGaA
Nestlé S.A.
Novartis Pharma AG
Osram GmbH
Robert Bosch GmbH
SAP AG
Schweizerische Bundesbahnen SBB
Schaeffler AG
Swisscom IT Services AG
ZF Friedrichshafen AG
Funder

other

Topic(s)
Business Case für Datenqualität
Anforderung durch neue Prozesse
rechtliche Anforderungen (Compliance)
Mess- und Berichtssysteme für Datenqualität
Rollen und Verantwortlichkeiten im Datenmanagement
Referenzprozesse im Datenmanagement
Kopplung von Datenmanagement- und Nutzungsprozessen
Prozess-Monitoring
Datensicherheit
Portal-/Workflow-Unterstützung für Datenmanagementprozesse
Systemarchitekturen
Datenmigration
Metadaten- und Informationsmodellierung
Gestaltungsprinzipien für Datenarchitekturen
Daten-Services
Überbetriebliches Datenmanagement
Standards
Public Processes
Method(s)
bilaterale Projekte
konsortiale Workshops
Fallstudien
Range
Institute/School
Range (De)
Institut/School
Division(s)

IWI - Institute of In...

Eprints ID
68049

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    Corporate Data Quality : Prerequisite for Successful Business Models
    (epubli, 2015)
    Otto, Boris
    ;
    Österle, Hubert  
    Data is the foundation of the digital economy. Industry 4.0 and digital services are producing so far unknown quantities of data and make new business models possible. Under these circumstances, data quality has become the critical factor for success. This book presents a holistic approach for data quality management and presents ten case studies about this issue. It is intended for practitioners dealing with data quality management and data governance as well as for scientists. The book was written at the Competence Center Corporate Data Quality (CC CDQ) in close cooperation between researchers from the University of St. Gallen and Fraunhofer IML as well as many representatives from more than 20 major corporations. The book is available in English and German as Open Access on http://www.cdq-book.org/
    Type:book
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/107386
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    Toward a Taxonomy of the Data Resource in the Networked Industry
    (BVL International, 2014-06-04)
    Otto, Boris  
    ;
    Abraham, Rene
    ;
    Schlosser, Simon  
    ;
    Delfmann, Werner
    ;
    Wimmer, Thomas
    The Internet of Things, the continuing globalization of logistics networks, decreasing product life cycles and increasing numbers of product variants are examples of current developments that pose, in general, new requirements both on networked industries and on data in logistical systems. Volume, heterogeneity and importance of data for businesses are growing. In order to be able to manage data under these complexity constraints, networked industries need a current, comprehensive and consistent understanding of the data architecture, i.e. of the key data entities, their relationships, their sources of origin, trustworthiness, frequency of occurrence, quality and ownership. As current approaches for data architecture management in particular and data resource management in general fall short in providing support for this endeavor, the paper at hand proposes a morphology of the data resource in networked industries. The morphology is the result of a taxonomic analysis aiming at providing structure to complex data environments. The paper uses four case studies to identify and describe the dimensions of the morphology and its characteristics. Furthermore, the paper develops the baseline of a method for guiding the application of the morphology.
    Type:conference paper
    Journal:Literature series economics and logistics
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/86826
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    A Reference Process Model for Master Data Management
    (Universität Leipzig, 2013-02-27)
    Reichert, Andreas  
    ;
    Otto, Boris  
    ;
    Österle, Hubert  
    ;
    Alt, Rainer  
    ;
    Franczyk, Bogdan
    The management of master data (MDM) plays an important role for companies in responding to a number of business drivers such as regulatory compliance and efficient reporting. With the understanding of MDM's impact on the business drivers companies are today in the process of organizing MDM on corporate level. While managing master data is an organizational task that cannot be encountered by simply implementing a software system, business processes are necessary to meet the challenges efficiently. This paper describes the design process of a reference process model for MDM. The model design process spanned several iterations comprising multiple design and evaluation cycles, including the model's application in three participative case studies. Practitioners may use the reference model as an instrument for the analysis and design of MDM processes. From a scientific perspective, the reference model is a design artifact that represents an abstraction of processes in the field of MDM.
    Type:conference paper
    Volume:1
    URL:http://ul.qucosa.de/api/qucosa%3A11917/attachment/ATT-0/
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/89595
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    Researcher-Practitioner Collaboration and Knowledge Transfer: Results from an Online Survey
    (University of St. Gallen, Institute of Information Management, 2012-07-01)
    Otto, Boris  
    ;
    Österle, Hubert  
    Researcher-practitioner collaboration has been receiving much attention in the de-bate about relevant Information Systems (IS) research. Successful collaboration be-tween researchers and practitioners requires the transfer of knowledge, both from research to practice and vice-versa. The working report presents the results of an online survey on researcher-practitioner collaboration among design science researchers. It does not aim at inter-preting the results, but rather forms as their documentation. The results can then be taken up in further research activities.
    Type:working paper
    Issue:BE HSG / CC CDQ / 30
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/91364
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    Principles for Knowledge Creation in Collaborative Design Science Research
    (Association for Information Systems, 2012-12-18)
    Otto, Boris  
    ;
    Österle, Hubert  
    ;
    Joey, F. George
    Design Science Research (DSR) advances the scientific knowledge base while at the same time leading to research results of practical utility. Several guidelines for DSR have been proposed to support researchers in their work. Collaborative forms of DSR require that knowledge be created across the boundaries of the research community and the practitioners community. Only little research, though, has been undertaken so far investigating the topic of knowledge creation in collaborative DSR settings. Answers to fundamental questions are still missing: What knowledge creation processes are used? What problems may occur during researcher-practitioner collaboration? This paper addresses the gap in literature by taking a knowledge creation perspective on DSR. Based on a literature review and findings from the field it proposes a set of principles for knowledge creation in collaborative DSR.
    Type:conference paper
    URL:http://aisel.aisnet.org/icis2012/proceedings/EngagedScholarship/3/
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/90565
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    Gestaltung der Datenversorgungskette: Referenzprozessmodell und Anwendungsbeispiel
    (Institut für Wirtschaftsinformatik, Universität St. Gallen, 2012-01-01)
    Ofner, Martin  
    Type:working paper
    Issue:BE HSG / CC CDQ / 13
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/92119
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    Controlling Customer Master Data Quality: Findings from a Case Study
    Baghi, Ehsan  
    ;
    Otto, Boris  
    ;
    Österle, Hubert  
    Data quality management plays a critical role in all kinds of organizations. Data is one of the most important criteria for strategic business decisions within organizations and the foundation for the execution of business processes. For the assessment of a company's data quality, to ensure the process execution and to monitor the effectiveness of data quality initiatives, data quality has to be monitored and controlled. This can be achieved by implementing a comprehensive controlling system for data quality. The implementation of such a system has been realized in only a few organizations. This paper presents a single case study describing the implementation of a comprehensive data quality controlling system. The study focuses on controlling activities defined in the fields of business management.
    Type:conference paper
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/116396
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