Rapidly Generate Millions Of Synthetic Data Records That Mimic Your Own To Support Your Quality Engineering Efforts

“We recently processed 44 million rows of data in less than three hours. That was estimated to take a team of people 40-50 days to do manually.” – iDataMaker Client

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Regulatory requirements in 2020 and beyond mean testing and developing on production data is too risky. iDataMaker can rapidly generate and obfuscation production-like data for your testing and data quality management purposes to de-risk and accelerate your projects.

What Is iDataMaker?

iDataMaker is deployed through the iData software solution, combining our expertise in Test Data Management with powerful profiling, data quality and data migration capabilities.

If you’re looking to:
• Obfuscate or “mask” elements of a product dataset
• Generate your own data for testing purposes
• Automate your testing processes

You could benefit from using iDataMaker to do so.

Remove human error with this automatic solution to support your testing and development and benefit from reliable, continuous test automation without the need to hire consultants and make them do mundane tasks. iDataMaker will empower you to run as many different test scenarios and testing strategies as you like, with a dataset based on your production scenarios.
Having a continuous quality feedback loop will speed up your real-time deployment process and allow you to have a complete understanding of your software before releasing it.

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What Is Test Data Management?

Test data management is the process of planning, designing, storing and then managing various test data management processes and methods. Effective test data management allows teams to have control over things like data, policies, rules and files during the testing cycle. Test data management splits test data and production data in two, allowing quality engineering to benefit from test data which simulates what exists in live. Data creation or obfuscation are vital alternatives to using production data, it is important that this test data is separated from production data to ensure that sensitive data, often found in production databases, can expose customers identity and result in the organisation failing GDPR compliant rules.

Test data management allows you to obfuscate personally identifiable information while still allowing you to have enough adequate test data to make informed decisions, to satisfy the quality criteria of your programme.

What Are The Benefits Of Test Data Management?

Effective test data management helps companies, organisations and institutions implement highly sophisticated quality engineering practices which create high-quality software that will perform well once it’s been deployed. Good test data management ensures that tests are created based on live scenarios to capture issues early and prevent problems happening in the future such as bug fixes and rollbacks. Overall, it can help reduce the total cost of change resulting in a is a fantastically cost-efficient software deployment process. Furthermore, in a world of GDPR and other data regulations, an automated test data management solution gives you the chance to garner information, further your data discovery with different test conditions and enhance your data set all without falling foul of data regulations.

Want To Automate Your Testing Process? Get In Touch!

If you want to automate your testing process, enjoy a testing cycle that creates various test scenarios, provides constant feedback and speeds up the release of your products all while being GDPR compliant, then get in touch and let us help you with iDataMaker. From data preparation and obfuscation right the way through to test results, test automation and more continuous testing, iDataMaker can do it all.

If you’re a business or institution based in the UK and want a single, scalable solution for automated data testing then get in touch with the team at ids today.

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Downloadable Resources

Download our whitepaper to learn about the future of continuous testing.

In this comprehensive and enlightening whitepaper, James Briers discusses what the real issues and inefficiencies are in delivering quality and walks a reader through real solutions which helps to lift the mist on the mechanics involved.


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Data Quality Engineering