The primary objective of this work is to develop a concept for a holistic data quality management which is based on formal data quality metrics and a well–defined process model. The extensive use of metadata provides a flexible adaptation to various application domains and a maximum degree of automation
Data quality is crucial in measuring and analyzing science, technology and innovation adequately, wh...
Data warehouses are complex systems that have to deliver highly-aggregated, high quality data from h...
Abstract. As a decision support information system, a data warehouse must provide high level quality...
Users querying a database system will have returned to them a set of data with no indication of the ...
Abstract — In the processes and optimization of information integration, such as query processing, q...
This paper describes a relational database tool, the Data Quality Knowledge Management (DQKM), which...
The growing relevance of data quality has revealed the need for adequate measurement since quantifyi...
Data quality management is a great challenge in today’s world due to increasing proliferation of abu...
For organizations data quality is a prerequisite for automated decision making and agility. To provi...
Data quality management is a great challenge in today’s world due to increasing proliferation of abu...
Data quality management is a great challenge in today’s world due to increasing proliferation of abu...
The goal of a data warehouse system is to provide a comprehensive overview of the data available in ...
Data quality management is a pressing issue in the adoption and implementation of Business Intellige...
Today, it is a well known fact that poor quality data is costing large amounts of money to corporati...
The data asset is increasingly becoming one of the top factors in securing organization success. Rec...
Data quality is crucial in measuring and analyzing science, technology and innovation adequately, wh...
Data warehouses are complex systems that have to deliver highly-aggregated, high quality data from h...
Abstract. As a decision support information system, a data warehouse must provide high level quality...
Users querying a database system will have returned to them a set of data with no indication of the ...
Abstract — In the processes and optimization of information integration, such as query processing, q...
This paper describes a relational database tool, the Data Quality Knowledge Management (DQKM), which...
The growing relevance of data quality has revealed the need for adequate measurement since quantifyi...
Data quality management is a great challenge in today’s world due to increasing proliferation of abu...
For organizations data quality is a prerequisite for automated decision making and agility. To provi...
Data quality management is a great challenge in today’s world due to increasing proliferation of abu...
Data quality management is a great challenge in today’s world due to increasing proliferation of abu...
The goal of a data warehouse system is to provide a comprehensive overview of the data available in ...
Data quality management is a pressing issue in the adoption and implementation of Business Intellige...
Today, it is a well known fact that poor quality data is costing large amounts of money to corporati...
The data asset is increasingly becoming one of the top factors in securing organization success. Rec...
Data quality is crucial in measuring and analyzing science, technology and innovation adequately, wh...
Data warehouses are complex systems that have to deliver highly-aggregated, high quality data from h...
Abstract. As a decision support information system, a data warehouse must provide high level quality...