Context-based Data Quality Metrics in Data Warehouse Systems

Towards Data Warehouse Quality Metrics

Organizations are adopting datawarehouses to manage information efficiently as “the” main organizational asset. It is essential that we can assure the information quality of the data warehouse, as it became the main tool for strategic decisions. Information quality depends on presentation quality and the data warehouse quality. This last includes the multidimensional model quality. In the last ...

A Strategy for Managing Data Quality in Data Warehouse Systems

High level data quality and the management of ensuring data quality is one of the key success factors for Data Warehousing projects. The following article describes an approach for Data Quality Management, which is based on theories as well as practical experiences. Starting from effects of insufficient data quality in practice, a definition for information, data and data quality will be worked...

Proactive data quality management for data warehouse systems

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 [ENG99; HEL00]. Still, ensuring high level data quality is one of the most expensive and time-consuming tasks to perform in data warehousing projects [HAE98]. Many data warehouse projects are discontinued due to insufficie...

Big Data Quality: From Content to Context

Over the last 20 years, and particularly with the advent of Big Data and analytics, the research area around Data and Information Quality (DIQ) is still a fast growing research area. There are many views and streams in DIQ research, generally aiming at improving the effectiveness of decision making in organizations. Although there are a lot of researches aimed at clarifying the role of BIG data...

Data Quality Problems and Proactive Data Quality Management in Data - Warehouse - Systems Research Paper