Best Test Data Management Tools for GitHub

Parasoft helps organizations continuously deliver high-quality software with its AI-powered software testing platform and automated test solutions. Supporting embedded and enterprise markets, Parasoft’s proven technologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software by integrating everything from deep code analysis and unit testing to UI and API testing, plus service virtualization and complete code coverage, into the delivery pipeline. 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 is the cloud solution for SAP & web apps test automation, like Salesforce: it has the power of simplicity, customization, and integration with the most CI/CD tools. Test cases are highly reusable and easily maintainable. Undertaking a software transformation journey is a high risk. We offer a simple yet powerful solution to minimize the risk and reduce the implementation resources up to 80%. All you need to do is to record a Business Process: user actions, test data, and technical information will be captured. The recording will be your unique source of truth for running Automated tests and Manual tests, but also for Learning. Check out the website to see how Qualibrate is reinventing test automation for SAP and web apps.

Today’s Agile DevOps teams need the ability to go faster. BMC Compuware File-AID provides a cross-platform file and data management solution that enables developers and QA staff to quickly and conveniently access necessary data and files instead of hunting around for them. In turn, developers devote less time to data-related tasks and spend more time developing new functionality and managing production problems. Rightsizing your test data provides confidence to make code changes without unintended consequences. Access all standard file types regardless of record length or format for application integration. Compare data files or objects to simplify the test results validation process. Reformat files by easily modifying an existing file format instead of starting from scratch. Extract and load related subsets of data from multiple databases and files & more.

Privacy engineering tools delivered to you as APIs. Synthesize and transform data in minutes. Build trust with your users and community. Gretel’s APIs grant immediate access to creating anonymized or synthetic datasets so you can work safely with data while preserving privacy. Keeping the pace with development velocity requires faster access to data. Gretel is accelerating access to data with data privacy tools that bypass blockers and fuel Machine Learning and AI applications. Keep your data contained by running Gretel containers in your own environment or scale out workloads to the cloud in seconds with Gretel Cloud runners. Using our cloud GPUs makes it radically more effortless for developers to train and generate synthetic data. Scale workloads automatically with no infrastructure to set up and manage. Invite team members to collaborate on cloud projects and share data across teams.

Enterprise synthetic test data solutions. In order to generate test data that accurately reflects the structure of your application or database, it must be easy to model and maintain each test data project as changes to the data model occur throughout the lifecycle of the application. Maintain referential integrity of parent/child/sibling relationships across the data domains within an application database or across multiple databases used by multiple applications. Ensure the consistency and integrity of synthetic data attributes across applications, data sources and targets. For example, a customer name must always match the same customer ID across multiple transactions simulated by real-time synthetic data generation. Customers want to quickly and accurately create their data model as a test data project. GenRocket offers 10 methods for data model setup. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.