An on-demand test data management strategy doesn’t just happen. Follow 6 key steps to ensure trusted test data is always accessible to your testing teams.
Table of Contents
1. Manage Test Data via Business Entities
An effective test data management strategy enables testing teams to systematically provision production-like, trusted data, for any test case, easily and on demand.
Instead of having to understand the complexities of source systems, databases, tables, and columns, testing teams should be able to simply define the business entities for which they need test data.
For example, it should be easy for a software testing team at a bank to provision test data for 300 customers that live in Florida, married with 2+ children, and that have a bank balance greater than $5,000. The testers would not have to know that the customer data is collected from, and provisioned into, 35 different systems.
2. Extract on the Fly
The second step to an agile test data management strategy is to enable the tester, or test data automation tool, to request the data needed to perform a given test, in flight, without any preparation.
When the required data is fragmented and dispersed across many different systems and data sources, test data management tools – that can integrate with the production systems, and extract test data according to predefined rules – can come in really handy.
3. Refresh and Sync
Testing is an iterative process. When bugs are discovered and fixed, continuous testing ensures quality.
The third step to a fresh test data management strategy is to provide testing teams with the means to quickly roll back the test data that was previously used – by the specific tester, for the specific use case – without impacting the test data currently being used for other tests.
Companies need a test data management system that is adaptable, easy to sync, and capable of refreshing data granularly for each component – while maintaining complete control.
The fourth step to a secure test data management strategy is to embed data masking (aka data anonymization) functionality in order to assure privacy compliance. When dealing with production data, the challenge is to protect sensitive data, while maintaining the its integrity and keeping it secure.
It’s critical to comply with privacy compliance regulations, and protect the data from breaches, with data masking tools (aka data anonymization tools). The ability to unify the test data from multiple sources, use anonymized data or de-anonymized data, as required, and secure it every step of the way, creates a simple and efficient process for meeting data compliance and security constraints.
The fifth step to a compliant test data management strategy is to allow for synthetic data generation when test teams can’t extract a sufficient volume of test data from production. Built-in synthetic-data generation tools enable testers to create artificial, yet highly representative, data.
High on the list of any test data management strategy should be the means to produce synthetic test data, based on real production data, while maintaining relational integrity of the data across all systems.
After acquiring the necessary test data, generating missing data, and masking it as required, it’s time to move it to the target test environments.
The sixth step to an on-demand test data management strategy should offer a fast and seamless path from multiple systems to multiple environments. Companies should be able to upload, adjust, and remove data scenarios and business entities at any stage throughout the process.
One System for All Your Test Data Management Strategy Needs
The entity-based test data management approach supports each of test data management strategy steps described above, with their unique ability to:
1. Create dynamic testing environments, on-the-fly, as part of testing automation
2. Enable unstructured data, such as voice, images, documents, etc.
3. Use any environment both as source and target
4. Reverse time, and “fix” faulty test data
5. Support hybrid (on-premise/cloud) testing environments
6. Migrate test data between data centers and the cloud
In short, they empower and support developers, testers, and DevOps teams, to accelerate software delivery, while improving the quality of the end product.
Learn more about K2view test data management tools.