A Data warehouse Testing Strategy for Banks

Abstract

Data Quality, Database Testing, and ETL Testing are all different techniques for testing Data Warehouse Environment. Testing the data became very important as it should be guaranteed that the data is accurate for further manipulation and decision making. A lot of approaches and tools came up supporting and defining the test cases to be used, their functionality, and if they could be automated or not. The most trending approach was the automating of testing data warehouse using tools, the tools started firstly by supporting only the automation of running the scripts helping the developers to write the test case just once and run it multiple times, then the tools developed and modified to automate the creation of the testing scripts and offer their service as a complete application that supports the creation and running of the test cases claiming that the user can work without the need of expertise and high technicality and just by being an end user using the tool’s GUI. Banking sector differs completely than any other industry, as data warehouse in banking sectors collects data from multiple sources and multiple branches with different data formats, and quality that should then be transformed and loaded in the data warehouse and classified into some data marts to be used in different dashboards and projects that depend on high quality and accurate data for further decision making and predictions. In this paper we propose a strategy for data warehouse testing, that automates all the test cases needed in banking environment