Broadcom Test Data Manager enables effective test data processes with tools for synthetic data generation, data masking, and data subsetting. It enhances automation and ensures data privacy and compliance, catering to diverse testing environments.
Broadcom Test Data Manager provides centralized data management with flexible functionalities like cubing and test matching, simplifying the creation and handling of test data. It supports both relational and non-relational data, optimizing test processes for effective results. Users find its intuitive UI and self-service portal time-saving. However, enhancements in programmatic capabilities, non-relational data handling, automation, and integration speed are needed. A unified web-based interface, better API usability, and expanded data source support could improve user experience. Mainframe functionality, data reservation, and web-based UI transitions also require focus for stability and scalability improvements.
What are its key features?
- Synthetic Data Generation: Create realistic test data without affecting actual records.
- Data Masking: Protect sensitive data through advanced masking techniques.
- Data Subsetting: Efficiently manage data volumes by extracting relevant data portions.
- Centralized Management: Simplifies data operations through a single management point.
- Flexible Functionalities: Offers cubing concepts and test matching for precise data targeting.
- Comprehensive Data Support: Handles both relational and non-relational data seamlessly.
What ROI benefits should you consider?
- Enhanced Automation: Streamlines test data processes, reducing manual effort and errors.
- Time Savings: Intuitive interfaces and self-service portals increase efficiency.
- Compliance Assurance: Adheres to data privacy norms, safeguarding sensitive information.
- Reduced Disk Usage: Efficient data subsetting decreases storage requirements.
- DevOps Integration: Seamlessly integrates with pipelines, accelerating testing phases.
Broadcom Test Data Manager is widely used in industries like healthcare and finance for data masking and test management. It aids in creating synthetic data, managing subsetting, and anonymizing information, particularly valuable in handling regulated data. Its alignment with DevOps and comprehensive data capabilities are key in supporting secure, efficient testing workflows.
Protegrity’s Data Protection Platform offers robust data security solutions tailored for enterprises seeking advanced data protection measures.
Designed for businesses needing comprehensive data protection, Protegrity’s Data Protection Platform provides encryption, anonymization, and monitoring to secure sensitive data across multiple environments. Its adaptability allows organizations to handle complex data privacy regulations.
What are the key features of Protegrity’s Data Protection Platform?
- Encryption: Safeguards data both at rest and in transit with sophisticated encryption technologies.
- Anonymization: Ensures compliance and privacy by anonymizing personal data.
- Monitoring: Continuous data activity monitoring helps in detecting suspicious activities and preventing breaches.
What benefits and ROI should users consider?
- Regulatory Compliance: Meets standards like GDPR and CCPA, reducing legal risks.
- Cost Efficiency: Minimizes data breach costs through effective data protection.
- Scalability: Supports growing data needs without compromising security.
Protegrity’s Data Protection Platform is particularly beneficial in sectors such as finance, healthcare, and retail, providing tailored security measures that protect sensitive customer data and foster trust. Its industry-specific solutions enhance data integrity and privacy, supporting organizations in maintaining competitive advantages.
