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Test Data Management

Automated workflow that capture, clone, mask and re-provision production data to create test data sets for test/dev environment for software development life cycle.

There is always a need for an improved software development life cycle that is faster, secure and cost-effective. With unprecedented demand and competition, frequency of software releases are like never before. To achieve quality and result oriented outcome, a proper testing strategy is critical. An effective strategy includes many components, test data management (TDM) is one among them. 

It is important that test data is highly available and easily refreshable to improve the software release cycle. It is also highly challenging that TDM meets regulations like GDPR (General Data Protection Regulation). Test data is not limited to production data, synthetic datasets that are required for testing should be part of test data sets. Hence TDM involves multiple phases. 

Data Cloning: Data is captured from the production environment and stored as images in TDM environment which are readily available for cloning. Data cloning is an instant operation as the production data sets are locally available. 

Realistic data Captured, Cloned, Masked & Re-provisioned for faster software life cycle

Data Masking: Production data comes with sensitive data like financial information, password, tokens, etc. It has to be masked before test datasets are created. 

Data subsetting & Synthetic Data: To test, it is not necessary to have all available production data. Data subsetting helps reduce storage and infrastructure cost comes with production data cloning. 

Provisioning: Once test data sets are ready, it will be made available to the test environment. TDM process ensures test data is available in the test environment at expected time and format. 

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Datagen Systems

Industry specialist in Data Management and modern data platform for AI/ML

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