Best Test Data Management Tools for GitHub

Parasoft's mission is to provide automated testing solutions and expertise that empower organizations to expedite delivery of safe and reliable software. A powerful unified C and C++ test automation solution for static analysis, unit testing and structural code coverage, Parasoft C/C++test helps satisfy compliance with industry functional safety and security requirements for embedded software systems.

Qualibrate, the cloud solution for SAP & Web Apps test automation, is like Salesforce. It has the power to be simple, customized, and integrate with most CI/CD tools. Test cases can be reused many times and are easy to maintain. It is risky to embark on a journey of software transformation. We offer a simple, yet powerful, solution to reduce risk and implement resources up to 80%. Recording a Business Process is all you have to do: user actions, test data and technical information will all be recorded. This recording will serve as your only source of truth for Automated and Manual tests, as well for Learning. Visit the website to learn more about Qualibrate's innovative approach to SAP and web app testing.

In today's fast-paced Agile DevOps environment, teams are increasingly required to enhance their speed and efficiency. BMC Compuware File-AID offers a versatile solution for file and data management across various platforms, allowing developers and QA personnel to swiftly and easily retrieve essential data and files without the need for exhaustive searches. This results in developers spending significantly less time on data management tasks and more time focused on creating new features and addressing production issues. By optimizing your test data, you can confidently implement code modifications without worrying about unforeseen effects. File-AID supports all standard file types, regardless of record length or format, facilitating seamless application integration. Additionally, it aids in comparing data files or objects, streamlining the process of validating test results. Users can also reformat existing files with ease, eliminating the need to start from the ground up. Furthermore, it supports the extraction and loading of relevant data subsets from various databases and files, enhancing overall productivity and effectiveness.

Gretel provides privacy engineering solutions through APIs that enable you to synthesize and transform data within minutes. By utilizing these tools, you can foster trust with your users and the broader community. With Gretel's APIs, you can quickly create anonymized or synthetic datasets, allowing you to handle data safely while maintaining privacy. As development speeds increase, the demand for rapid data access becomes essential. Gretel is at the forefront of enhancing data access with privacy-focused tools that eliminate obstacles and support Machine Learning and AI initiatives. You can maintain control over your data by deploying Gretel containers within your own infrastructure or effortlessly scale to the cloud using Gretel Cloud runners in just seconds. Leveraging our cloud GPUs significantly simplifies the process for developers to train and produce synthetic data. Workloads can be scaled automatically without the need for infrastructure setup or management, fostering a more efficient workflow. Additionally, you can invite your team members to collaborate on cloud-based projects and facilitate data sharing across different teams, further enhancing productivity and innovation.

Enterprise synthetic test data solutions. It is essential that test data accurately reflects the structure of your database or application. This means it must be easy for you to model and maintain each project. Respect the referential integrity of parent/child/sibling relations across data domains within an app database or across multiple databases used for multiple applications. Ensure consistency and integrity of synthetic attributes across applications, data sources, and targets. A customer name must match the same customer ID across multiple transactions simulated by real-time synthetic information generation. Customers need to quickly and accurately build their data model for a test project. GenRocket offers ten methods to set up your data model. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.