An ETL Metadata Model for Data Warehousing - Rahman, Nayem; Marz, Jessica; Akhter, Shameem (Journal of computing and information technology, 2012)
Meta-data 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 meta-data model is important to the implementation of a data warehouse; the lack of a meta-data model can lead to quality concerns about the data warehouse. A highly successful data warehouse implementation depends on consistent meta-data. This article proposes adoption of an ETL (extract-transform-load) meta-data model for the data warehouse that makes subject area refreshes meta-data-driven, loads observation time-stamps and other useful parameters, and minimizes consumption of database systems resources. The ETL meta-data 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.