An ETL Metadata Model for Data Warehousing
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| Title | An ETL Metadata Model for Data Warehousing |
| Authors | |
| Abstract | Metadata is essential for understanding information stored in data warehouses. It helps increase levels of adoption and usage of data warehouse data by knowledge workers and decision makers. A metadata model is important to the implementation of a data warehouse, the lack of a metadata model can lead to quality concerns about the data warehouse. A highly successful data warehouse implementation depends on consistent metadata. This article proposes adoption of an ETL (extracttransform-load) metadata model for the data warehouse that makes subject area refreshes metadata-driven, loads observation timestamps and other useful parameters, and minimizes consumption of database systems resources. The ETL metadata model provides developers with a set of ETL development tools and delivers a user-friendly batch cycle refresh monitoring tool for the production support team. |
| Publisher | University of Zagreb, University Computing Centre - SRCE |
| Date | 2012-08-06 |
| Source | Journal of Computing and Information Technology Vol 20, No 2 (2012) |
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