Identifying Prime Testing Zones To Ensure Quality ETL Routine Of A Data Warehouse

Attaining high quality accurate data for decision making is a major challenge for the data warehouse industry. The organizations practicing data warehouse are diverse in their functionality and follow varying business practices. To tackle the data quality and data management issues which are inherent in data warehouse implementation, the project team has to develop an extensive reviewing process for improving data quality. A thorough business practice review, an analysis of existing data quality and data cleansing techniques are necessary to develop a data quality assurance methodology. The quality assurance for an in house developed the extraction transformation and loading (ETL) routine using hand coded algorithms is not an easy task. This low level implementation of ETL logic may cause hidden errors at technical as well as at logical level. Hence instigation of automated testing procedures as an integrated module of ETL routine itself is essential to ensure a high quality data in a data warehouse. The identification of such crucial test cases which may be automated to enhance data quality in a data warehouse is the sole aim of this paper.