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A sophisticated method is indispensable to manage such huge volumes of data. Thatu2019s where artificial intelligence comes into play. Therefore investing in AI-based testing tools is the need of the hour. Hire the best DataOps, TDM, and DevOps solutions to achieve the ultimate outcome you desire.
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What is Test Data Management? Test data management involves managing data required for running automated tests with minimal human or manual intervention. TDM Phases TDM involves 5 different phases- • Planning phase • Analysis phase • Design phase • Build phase • Maintenance phase
Planning Phase Planning phase involves the following- • Forming a test data management team and assigning a test data manager • Defining necessary datasets for data management • Preparing the required documentation, including the list of tests and obtaining the necessary authorisation. Analysis Phase Activities of the analysis phase include- • Consolidation and collection of test data requirements • Defining critical policies for data backup, access authority, and storage.
Design Phase The design phase includes- • Data distribution • Test activities • Coordination/communication • Document for the data plan Build Phase In this stage, the TDM process finally gets implemented. It includes- • Execution of all the plans prepared in the previous steps. • Data masking • Data backup.
Maintenance Phase Once the TDM process is implemented, firms need to maintain continuous and rigorous maintenance. The process includes • Troubleshooting and fixing issues with the test data tools or process • Updated existing data as required • Add new data Hire the best DataOps solutions for optimum results.
Why Is Test Data Management Important? Automated Testing Demands For Quality Data No matter how excellent your testing strategy is, feeding incorrect or bad data will get you bad results. Not taking care of the quality of your test data would be financially draining. All investments made into your testing strategy will be gone to waste. Automated Testing Requires Available Data Another vital responsibility of TDM is ensuring the availability of the test data. Even if the highest quality data is not available when required, it becomes useless. The only worst scenario would be to have readily available low-quality data. Therefore you’ll always need high-quality data which is readily available. You cannot compromise with either quality or availability.
Your Business Needs To Comply With Data Regulations Exposing sensitive data can be catastrophic for any business. You need to adhere to various data laws and regulations enlisted by governing authorities (GDPR, PCI DSS, etc.). Failing to comply with the data regulations may lead to lawsuits and impair your brand image. Finding Bugs At The Earliest Is Of Utmost Importance The sooner you’re able to detect a bug, the cheaper and easier it is to fix it. With a robust test data management process, you can be assured that the whole automated testing process runs smoothly and increases the chance of detecting more bugs earlier. To stay afloat in the competitive world, you need to adopt and master the process of test data management. Test data management is still a considerable challenge for many enterprises. With innovation in the software development process, a massive amount of data is generated and required. A sophisticated method is indispensable to manage such huge volumes of data. That’s where artificial intelligence comes into play. Therefore investing in AI-based testing tools is the need of the hour. Hire the best DataOps, TDM, and DevOps solutions to achieve the ultimate outcome you desire.
