Toward total data quality management (TDQM)
Information technology in action
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
A product perspective on total data quality management
Communications of the ACM
Enhancing data quality in data warehouse environments
Communications of the ACM
Improving data warehouse and business information quality: methods for reducing costs and increasing profits
Data on the Web: from relations to semistructured data and XML
Data on the Web: from relations to semistructured data and XML
Communications of the ACM - Supporting community and building social capital
Benchmark Handbook: For Database and Transaction Processing Systems
Benchmark Handbook: For Database and Transaction Processing Systems
Data Quality for the Information Age
Data Quality for the Information Age
Fundamentals of Data Warehouses
Fundamentals of Data Warehouses
AIMQ: a methodology for information quality assessment
Information and Management
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Assessing data quality with control matrices
Communications of the ACM - Information cities
Methods for evaluating and creating data quality
Information Systems - Special issue: Data quality in cooperative information systems
Information Systems - Special issue: Data quality in cooperative information systems
Completeness of integrated information sources
Information Systems - Special issue: Data quality in cooperative information systems
Data Quality: Concepts, Methodologies and Techniques (Data-Centric Systems and Applications)
Data Quality: Concepts, Methodologies and Techniques (Data-Centric Systems and Applications)
From Unstructured Data to Actionable Intelligence
IT Professional
Quality-driven query answering for integrated information systems
Quality-driven query answering for integrated information systems
Methodologies for data quality assessment and improvement
ACM Computing Surveys (CSUR)
AMT'12 Proceedings of the 8th international conference on Active Media Technology
Data quality assessment: The Hybrid Approach
Information and Management
Hi-index | 0.00 |
Measuring and improving data quality in an organisation or in a group of interacting organisations is a complex task. Several methodologies have been developed in the past, providing a basis for the definition of a data quality programme that guarantees high data quality levels. Since the main limitation of existing approaches is their specialisation on specific issues or contexts, this paper presents a Comprehensive Data Quality (CDQ) methodology. The main aim of the CDQ methodology is the integration and enhancement of the phases, techniques and tools proposed by previous approaches. In particular, the CDQ methodology is conceived to be at the same time complete, flexible and simple to apply. Completeness is achieved by considering an existing techniques and tools and integrating them in a framework that can work in any organisation. The methodology is flexible, since it supports the user in the selection of the most suitable techniques and tools within each phase and in any context. Finally, CDQ is simple, since it is organised in phases and each phase is characterised by a specific goal and a set of techniques to apply. The methodology is explained by means of a running example and significant cases of its application are reported.