IBM Optim Test Data Management use cases
Review some key use cases for IBM® Optim Test Data Management.
IBM Optim Test Data Management provides AI-ready test data with production-like datasets across hybrid environments for AI/ML use cases, automated provisioning, and CI/CD integration. The following use cases illustrate how IBM Optim addresses common challenges in test data management and enables AI/ML training with secure, realistic data.
Discovering and provisioning related data
Challenge: Data engineers often need to manually prepare data from production systems for multiple application teams. This process is time-consuming and can lead to delays.
Solution: IBM Optim discovers data relationships and hidden correlations across multiple sources to locate and provision relevant test data. IBM Optim creates consistent, referentially intact test data based on business objects and creates logical relationships across disparate data for referential integrity.
- Provide realistic, consistent datasets for testing, development, and QA environments.
- Automate discovery of related tables, eliminating manual mapping and reducing defects caused by missing or mismatched data.
- Optimize operational costs.
Creating targeted test data without cloning production databases
Challenge: Application teams need scenario-specific test cases without creating full production copies.
Solution: IBM Optim creates production-like, right-sized, and targeted test data without cloning the entire production database. IBM Optim supports complex selection rules for specific business scenarios while preserving referential integrity. You can create right-sized, masked subsets using advanced filters to mirror complex business rules.
- Model test data on complex business rules and edge scenarios for improved test coverage.
- Optimize test data volumes to reduce storage and infrastructure costs.
Rapid provisioning and refresh for agile development and CI/CD integration
Challenge: Development and QA teams need the ability to quickly provision and refresh test data across multiple environments and applications to support agile development and continuous integration/continuous delivery (CI/CD) pipelines.
Solution: With IBM Optim, you can provision and refresh data on-demand across diverse data sources. IBM Optim enables reusable test data across multiple application teams and environments for iterative test cycles, and supports role-based access control to help protect your data. IBM Optim provides API-driven execution for high-volume, scalable workloads and CI/CD pipelines with automated provisioning across on-premises, AWS, Azure, GCP, and other hybrid environments.
- Deliver high-quality, standardized test environments across application teams.
- Accelerate time to market and streamline test data delivery for agile development.
- Enable reusable parquet test datasets for faster testing cycles.
- Integrate seamlessly with CI/CD pipelines for continuous delivery with zero data leakage.
AI/ML model training with production-like datasets
Challenge: AI/ML teams need high-quality, production-like datasets for training models, but using actual production data poses security and compliance risks. Creating realistic training data manually is time-consuming and may not accurately represent production scenarios.
Solution: IBM Optim provides scenario-specific, production-like datasets for AI/ML training based on complex business rules. The solution delivers referentially intact, secure test data that mirrors production data characteristics without exposing sensitive information. IBM Optim enables realistic training data without production data exposure, supporting AI/ML training, RAG context, vector embeddings, and other AI/ML use cases.
- Train AI/ML models with high-quality, production-like data for improved model accuracy.
- Accelerate AI/ML development cycles with readily available, secure training datasets.
- Support diverse AI/ML use cases including RAG systems, vector stores, and model training.
- Ensure data security and compliance while enabling realistic AI/ML training scenarios.
Application testing and modernization
Challenge: Development teams need to test applications thoroughly before deployment, including testing during application modernization initiatives. Testing requires realistic data that represents various scenarios without compromising security.
Solution: IBM Optim provisions reusable test data across multiple teams for application testing and modernization projects. The solution rapidly provisions data across diverse data sources and enables reusable parquet test datasets, supporting DevOps and application modernization initiatives with zero data leakage.
- Accelerate application testing with readily available, production-like test data.
- Support application modernization initiatives with secure, realistic datasets.
- Enable faster testing cycles through reusable test data across multiple teams.
- Reduce infrastructure costs by optimizing test data volumes.
Securing sensitive data through masking
Challenge: QA teams require realistic test data to validate functionality, but regulations such as GDPR and HIPAA prohibit using actual customer data. Additionally, AI/ML teams need realistic training data without exposing sensitive production data.
Solution: IBM Optim enables you to implement consistent, context-aware data de-identification by using predefined masking policies. IBM Optim retains the format and usability of original data, ensuring that masked values remain realistic for testing and reporting. You can use IBM Optim with custom scripts and user-defined functions to achieve your advanced masking requirements. IBM Optim masks complex data like credit cards and SSNs using predefined masking policies and masking APIs.
- Protect sensitive data and reduce the risk of exposure.
- Mask data consistently with application and business logic while preserving data format, usability, and referential integrity.
- Preserve referential integrity across relational databases and data lakes.
- Ensure compliance with data privacy regulations and enterprise governance policies.
- Enable compliant training data without manual redaction and data masking.
Enforcing compliance with masking policies
Challenge: Analytics teams require real production data for accurate insights, but safeguarding personally identifiable information (PII) is essential to avoid compliance violations. Organizations need to support regulatory compliance and sovereign controls while enabling data analysis.
Solution: IBM Optim includes predefined, format-preserving masking policies for industry-standard fields such as social security numbers and credit card numbers. IBM Optim also supports compliance reporting to validate the enforcement of data privacy policies. The solution provides automated compliance for GDPR, HIPAA, SOX, and PCI-DSS requirements with audit trails and sovereignty controls.
- Enabling safe data sharing and preventing data breaches.
- Minimizing litigation risk by ensuring compliance with global data protection laws.
- Supporting regulatory compliance and sovereign controls requirements.
- Enabling production data for analytics with predefined masking policies.
- Securing production data and preventing data exposure.