engleski

Data warehouse and data quality – an overview

Almost every company today is collecting and storing data for later analysis and business decision making in some kind of repository, usually a data warehouse. In order for decision to be timely and accurate (content-wise), it should be based on high quality data. Data quality policies and standards can be applied to every data warehouse. However, every data warehouse is unique and there is a need to consider a lot of criteria to achieve the best outcome. The goal of this paper is mostly to give an overview of data quality issues in a data warehouse, explain different criteria and categories for data quality and show some causes and consequences of saving low quality data in the data warehouse. The main contribution of this paper is, consequently, an overview of data quality issues in the context of data warehouses and an insight into some new and emerging research areas in the field of data warehouse quality.

data warehouse ; data quality ; database ; ETL ; data model

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