Anchoring data quality dimensions in ontological foundations
Communications of the ACM
Putting the enterprise into the enterprise system
Harvard Business Review
Improving data warehouse and business information quality: methods for reducing costs and increasing profits
Enterprise resource planning: ERP system migrations
Communications of the ACM
Data resource quality: turning bad habits into good practices
Data resource quality: turning bad habits into good practices
Enterprise knowledge management: the data quality approach
Enterprise knowledge management: the data quality approach
Data Quality for the Information Age
Data Quality for the Information Age
Information Systems Frontiers
Data Quality: The Accuracy Dimension
Data Quality: The Accuracy Dimension
The SAP R/3 Guide to EDI and Interfaces
The SAP R/3 Guide to EDI and Interfaces
Information and Management
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Master data is a main component of most information systems. In distributed and heterogeneous organizations, problems of data quality may arise if several Enterprise Resource Planning (ERP) systems, customized with respect to local business needs and objectives, use subsets of common master data. In this paper we describe data management issues in a large organization, running 10 instances of the SAP R/3 system. For coordinating purposes, com mon elements of materials master data are entered via a centralized application and subsequently distributed to the affected instances. However, this master data management approach did not avoid massive data quality problems, which are, for instance, hampering the computation of informative key performance values and the effective realization of inventory reduction programs. The paper discusses possible approaches for improving data quality in this situation and in other cases of distributed ERP systems.