Moving data and applications from on-premises to a cloud or from one cloud platform to another? Strengthen your Cloud Data Migration Testing Strategy with Datagaps’ Great Data Platform which helps you perform comprehensive testing to check if your data remain functional, stable, scalable and compatible in the target cloud environment.
Data Migration projects often involve schema conversion tasks such as converting database columns from one data type to another. Issues with schema conversion can result in loss of data and migration failures. Datagaps ETL Validator and Dataflow can help automate schema metadata comparison across heterogeneous data sources. Datagaps automatically retrieves metadata for all the supported data sources thus making it easy to create tests for validating them.
Cloud Data Migration can be done in multiple strategies such as Lift and Shift, Application Refactoring or Re-platforming. No matter what strategy is used, it is imperative to validate that the data migrated completely and as expected. Datagaps ETL Validator provides a Data Migration wizard for automatically generating test cases. Using this wizards, hundreds on test cases can be created withing a few minutes. For large volumes, Datagaps Dataflow is capable of comparing billions of records using apache spark as the engine. Datagaps makes it easy to achieve 100% data validation for data migration projects.
Once the initial data load has been performed, incremental data syncs are run for migrating changes until the application migration has been completed and the legacy applications are switched off. Datagaps can automate the validation of incremental data loads, In addition, ETL Validator offers Data Profile and Checksum test cases that can be very helpful in validating data without comparing every single record on a periodic basis. These test cases can be added to a test plan and invoked from your CI/CD process.
ETL Validator comes with an inbuilt ETL engine capable of extracting and comparing millions of records from multiple data sources while executing test cases in parallel. ETL Validator connects to a wide variety of data sources. And we are constantly adding support for many modern data sources.
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