"ETL Testing" as part of Data Quality Assurance processes in a non-production environment and "Production Data Monitoring" as part of ongoing Data Quality Control processes in a production environment may sound like two different solutions, but technically, both are more of same. The goal is to test the data flow, and validate and reconcile the data at each and every hop on its way from the source systems till it reaches the digital dashboards. Extract-Transform-load (ETL) is a vital IT function in any organization as it deals with one of the most valuable assets — "Data".
ETL processes are used for populating data into the data warehouse from one or more source systems in addition to moving between data sources, applications and systems. Hence, there is a great need for testing the ETL processes to ensure that they work correctly before they get deployed into productive use.
Verification, validation and certification of the ETL development are prerequisites to meeting the data integration requirements. It is also important to establish automated data control processes to ensure data validity, integrity and reliability on a continuous basis in productive operation.
5 Stages of ETL Testing
- Identify data sources and requirements: ETL testers must understand all involved data sources and the transformation required between them and the target system. Testers will record data sources to confirm all data was moved.
- Acquire data: Testers will extract data from the sources and ensure extraction is proper and complete.
- Implement logic and dimensional modeling: After extraction, data undergoes transformation to create the appropriate format and align with business rules for the target system.
- Build and populate data: Following transformation, data is ready to be populated in the target system.
- Create reports: Once the process is complete, documentation is essential to identify issues or bugs with records and find ways to fix them.
Why You Need ETL Testing
ETL testing confirms that data has been extracted and transformed completely and correctly. It also ensures all data is in the correct format and prevents quality issues that can arise from data migration. With ETL testing tools, your operation can guarantee quality data extraction and warehousing. You might use ETL testing after:
- Setting up a new data warehouse
- Adding a new data source to your warehouse
- A data migration or integration project.
- Moving data for any reason
- Suspecting issues with data quality or ETL processes
Prevent flaws in your data warehousing, mitigate the risk of bugs, and keep your migration and integration processes efficient with ETL testing.
The Importance of ETL Tools in Data Warehousing
The more an organization relies on data warehousing, the more essential ETL tools are. These tools can collect, read and migrate significant volumes of data from multiple sources, and ETL testing tools ensure every process happens correctly and safely each time. With ETL monitoring tools, your operation can:
- Identify issues with source information or business rules before stacking data in the target system
- Support reliable transfer of bulk data to target systems
- Prevent duplication and loss of data
- Eliminate potential human and system errors during data migration so your operation can rely on your data warehouse for accurate information and ongoing business insights.