ETL stands for Extract-Transform-Load and it is a process of how data is loaded from the source system to the data warehouse. Data is extracted from an OLTP database, transformed to match the data warehouse schema and loaded into the data warehouse database.
Data warehouse testing concentrates on more than just the critical potentially error-prone ETL stage, where bugs can pollute the whole system. Data Warehouse Testing and ETL Testing are considered synonymous. ETL Testing tests the whole warehouse, not just the ETL data-addition stage.
Historical data is becoming a key tool for decision-making at enterprises of all levels. With burgeoning data, most organizations are investing in building a robust data warehouse using latest tools. However, testing the data accuracy, performance, and security becomes complicated and needs a comprehensive approach to ensure the success of your DW and BI implementation
Particularly, the role of QA is very challenging in this context, as this is still in a nascent stage. Testing Data Warehouse & ETL applications requires a specific mindset, skillset and deep understanding of the technologies, and pragmatic approaches to data. Data Warehouse & ETL from a tester’s perspective is an interesting aspect. Understanding the evolution of Data Warehouse & ETL, What is Data Warehouse & ETL meant for and Why Test Data Warehouse & ETL Applications is fundamentally important.
CariKture India has extensive experience in Analytics Testing, DW, and Big Data testing engagements and addresses the unique challenges of DW and Big data analytics testing. We test the DW applications at all levels, starting from data source to the front-end BI applications and ensure the issues are detected at the early stages of testing. We ensure that the Big Data testing solution is adequately automated and scalable to meet future business needs.
Our Testing approach includes the following strategies:
And using the above approach, we achieve the following: