Proactive Data Quality Management for Data Warehouse Systems - A Metadata based Data Quality System
Markus Helfert, Clemens Herrmann
Abstract
Open-access reader
Markus Helfert, Clemens Herrmann
Abstract
Open-access reader
Data warehousing has captured the attention of practitioners and researchers for a long time, whereas aspects of data quality is one of the crucial issues in data warehousing. Still, ensuring high level data quality is one of the most expensive and time-consuming tasks to perform in data warehousing projects. Many data warehouse projects are discontinued due to insufficient data quality. The following article describes an approach for managing data quality in data warehouse systems through a metadata based data quality system. The results are integrated in a comprehensive management approach and are based on practical experiences within a Swiss bank.
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Data warehousing has captured the attention of practitioners and researchers for a long time, whereas aspects of data quality is one of the crucial issues in data warehousing. Still, ensuring high level data quality is one of the most expensive and time-consuming tasks to perform in data warehousing projects. Many data warehouse projects are discontinued due to insufficient data quality. The following article describes an approach for managing data quality in data warehouse systems through a metadata based data quality system. The results are integrated in a comprehensive management approach and are based on practical experiences within a Swiss bank.
Key concepts: Data warehouse, Metadata, Data quality, Computer science, Data governance, Metadata management, Quality (philosophy), Database