Smart Test Data Automation
Validata Sense.ai’s test data management capabilities solve your test data needs, by integrating data compliance with data delivery, and providing ‘fit for purpose’, secure data on demand. Take advantage of advanced masking and synthetic test data generation for your teams, whenever and wherever they need it.
By using advanced algorithms that identify data ‘frequent episodes’, it recommends the best datasets to be used in your test scenarios for maximum test data coverage, against risk and business needs.
CHALLENGES
Simplify complex application landscapes and overcome test data management challenges
Most organisations face challenges in accessing the right combinations of non-production data, yet having immediate access to complex and relevant data is crucial. This necessity is evident in the frequent software releases driven by customer demand, which rely on continuous testing. Effective continuous testing and DevOps initiatives, in turn, depends on instant availability of the right test data.
Production data only provide as much as 20% functional coverage, focusing testing only on the ‘happy paths’, which means that defects will invariably make it into production, leading to rework, critical delays, increased costs, and potential project failure.
Using production data for testing and development purposes is subject to strict regulations, like GDPR, PCI and HIPAA.
Using traditional data masking tools to anonymize production data for testing endangers privacy, affects data integrity and does not guarantee compliance.
Testers usually spent 60% of their time searching for or waiting for data. Provisioning and refreshing test data is time-consuming because of its size, the complexity and the number of people involved in the process.
Long waiting times have a negative impact on your projects and the overall time to market.
Many banks are using full size copies of production environment for development, testing, reporting and training.
With the production environments growing every day, your development and testing environments also grow significantly which results in high storage, admin and license costs.
Automate delivery of secure test data for Agile, DevOps, and CI/CD.
Data from any source both on-premise and cloud
Data with data catalog, data lineage, version and audit control
Sensitive Data for security and compliance
Data pipelines end-to-end
Proven ROI
Deliver Data for DevOps in Minutes Not Days
Smart use of test data is the catalyst to innovation
Synthetic Test Data Generation: Generate ‘fit for purpose’, realistic, quality data
Through a powerful synthetic data generation engine, it provides testers with data before testing starts; realistic data tailored to their specific testing and development needs.
It can rapidly generate large sets of synthetic test data to eliminate the risk of data breach by creating production-like data but without the sensitive content.
As a result, the synthetic test data set have the same power as the real data but none of the privacy concerns that impose user restrictions, and can also help resolve infrastructure, storage and system constraints.
Data Masking: Ensure compliance and data security
The platform can automatically identify and anonymise sensitive data before it’s provisioned to non-production environments, to avoid data breaches and ensure regulatory compliance.
It features a data profiling functionality that understands the complex data structures and formats enabling users to automatically identify those fields that contain sensitive data values.
Leveraging data masking algorithms, that do not require programming or coding skills, it is able to irreversibly mask this sensitive data at high speed, allowing faster security and compliance even in large environments without affecting overall delivery schedules. It is able to mask everything such as names, social security numbers, addresses, etc, and the algorithms can be configured to match specific client needs and security policies.
- Maintain referential integrity: Ensure consistency and accuracy of your masked data across applications, preserving the relationships between data elements for reliable testing
- Comply with regulations: Meet the requirements of various data privacy regulations
Version control all data for testing
- Audit and version control for all datasets. Bookmark data and link them with test cases.
- Use masked or synthetic data when required
- Easily add, delete, and share test data
Collaborative Test Environment Management
Most firms use multiple different environments for testing their applications. Managing this is costly and inefficient and data must be provisioned to multiple development and other environments across institutions.
Imagine an organization that has a production database of 20TB and also have and maintain more than 40 environments for their testing and development projects. The cost for the infrastructure and for the maintenance of these environments is huge and is continuously growing along with the databases’ size.
The platform enables the fast delivery of secure, personalized data environments with masked and secure data in minutes across on premise, private and public clouds, addressing the data friction in the CI/CD process.
It features a self-service booking engine that amongst others, it allows to:
- Book an environment and associate it with a release.
- Intelligently search across the entire environment inventory.
- View approval status and potential conflicts with other project or releases.
- Define role-based permissions and access.
- Track dependencies and centrally define test environment relationships, including child associations
BENEFITS
Eliminate Data Bottlenecks and fix the ‘Data Gap’ in QA and DevOps
Accelerate speed, quality, and compliance
Reduced environment-related bugs and provisioning delays by 80%
Reduces the time and resources required to provide data ‘fit for purpose’ by 60%
Reduce Storage, Infrastructure Costs and Admin Overheads for managing data and environments
Increases Developers’ & QA’s productivity by providing the test data early
Improves test data coverage and reduces the overall cost of testing
Accelerate testing and Development cycles
Secure, Self-service Access: Testers can now be more self-sufficient to provision their own test data
