Data Quality Testing: Data Quality Tests includes syntax and reference test. Multiple SQL queries need to be run for each row to verify the transformation rules.Ĩ. It cannot be achieved by writing one source SQL query and comparing the output with the target. Data Transformation Testing: Data transformation testing done in many cases. Data Accuracy Testing: This testing is done to ensure that the data is accurately loaded and transformed as expected.ħ. Metadata Testing: Metadata testing includes the measurement of types of data, length of data, and check index/constraint.Ħ. This type of testing checks the extracted data from an older application are precisely same as the data in a new application.ĥ. Application Upgrade: This type of ETL testing is automatically generated, which saves the test development time. Source to Target Testing (Validation): This type of testing is done to validate the data values transformed the expected data values.Ĥ. Informatica Data Validation option provides the automation of ETL testing and management capabilities to ensure that the data do not compromise production systems.ģ. Production Validation Testing: This testing is done on data when data is moved to production systems.
Business Analyst: Business Analyst gathers and documents the requirements.Here are the responsibilities which are played by different groups: However, the new data warehouse is built and verified with the help of ETL tools. In this testing, the input is taken from the customer's requirement and different data sources. New Data Warehouse Testing: It is built and verified from the core. Implement dimensional modeling and business logic.ġ.ETL testing identifies data sources and requirements.Like other testing process, ETL testing also go through some testing processes.
RESOURCE GOVERNOR TO CONTROL ETL PROCESSES VERIFICATION
It involves the verification of data at various stages, which is used between source and destination.
ETL testing is different from Database testing in terms of its scope and the steps followed during this testing.ĮTL testing is to ensure that the data which has been loaded from a source to destination after transformation is accurate. It is also called as table balancing or product reconciliation. It also involves the verification of data at various stages that used between source and destination ETL (Extraction, Transformation and Loading) TestingĮTL testing is done before data is moved to production data warehouse systems. Our ELT Testing tutorial is designed for beginners and professionals.ĮTL tools extract the data from all the different data sources, transforms the data and (after applying joining fields, calculations, removing incorrect data fields etc.) and loads it into a data warehouse.ĮTL testing is done to ensure that the data has been loaded from a source to destination after business transformation is accurate. ELT Testing tutorial provides basic and advanced concepts of ELT Testing.
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