Wende, KristinKristinWendeIsari, DanielaD'Atri, AlessandroWinter, Robert2023-04-132023-04-132007-06-06https://www.alexandria.unisg.ch/handle/20.500.14171/80585Enterprises need data quality management (DQM) to respond to strategic and operational challenges demanding high-quality corporate data. Hitherto, companies have assigned accountabilities for DQM mostly to IT departments. They have thereby ignored the organisational issues that are critical to the success of DQM. With data governance, however, companies implement corporate-wide accountabilities for DQM that encompass professionals from business and IT. This paper proposes a contingency approach to data governance. It outlines a data governance model based on IT governance research. The model comprises a first set of data quality roles, decision areas and responsibilities. The data governance model documents the data quality roles and their type of interaction with DQM activities. In addition, the paper identifies contingencies and their impact on the model configuration. Companies can implement their company-specific data governance model based on these findings.enData GovernanceDataqualitätDatenqualitätsmanagementconference paper