Enterprises use data warehouses to accumulate data from multiple sources for analysis and research. A data warehouse is populated using the Extract, Transform, and Load (ETL) process that extracts data from various sources, integrates, cleans, and transforms it into a common form, and loads them into the data warehouse. Faults in the ETL implementation and execution can lead to incorrect data in the data warehouse, which renders it useless irrespective of the quality of the applications accessing it and the quality of the source data. Thus, ETL processes must be thoroughly tested to validate the correctness of the ETL implementation. This project develops and evaluates two types of functional testing approaches, namely data quality, and balancing tests. Data quality tests validate the data in the target data warehouse in isolation and balancing tests check for discrepancies between the source and target data.
We, at QO-BOX, brings you a varied expertise in this area and support you by conducting a thorough analysis of your existing Warehouse Functions and the as-is data and bring you an Out-of-the Box solution to transform your current system into an Industry ready system.