DataPlus for consistent policy-based data masking, data pseudonymization and test data generation
TCS MasterCraft™ DataPlus is an integrated data management software, which provides data privacy and test data provisioning, to enable trusted data sharing for enterprises.
Data protection regulations across the globe require enterprises to ensure privacy of data, when data is shared or accessed. Many enterprises have setup a formal data privacy program, as part of their larger data protection regulatory compliance. For enterprises wanting to ensure data privacy as part of their IT Development Operations and other privacy-safe data provisioning requirements, DataPlus provides:
- ML-based Sensitive Data Attribute Discovery, for automatically discovering potential sensitive and personally identifiable business data elements, from organization data stores, in an intelligent and policy-driven approach.
- Rich collection of Pre-packaged Data Masking Rules, that are well suited for handling data masking requirement of different types of business data elements and generate fictitious yet realistic masked values.
- Pre-packaged and Configurable Data Masking Policies, that bring about automation and a governed approach of setting up data masking process.
- Multiple approaches of privacy-safe test data generation, such as Static Data Masking, Data Pseudonymization, Synthetic Data Generation and Voluminous Data Generation, that help create right-sized test data for multiple application testing scenarios
- Data sub-setting that limits the amount of data utilized in development environments for testing purpose.
- Support for heterogeneous data source technologies on premise and cloud and diverse application technology platforms.
Privacy-safe test data generated by DataPlus can be used for various use-cases such as privacy-safe IT development operations, application performance/stress testing, data migration testing, privacy-safe data analytics, among others. DataPlus’ privacy-safe data provisioning features are of immense interest to enterprise roles such as Data Privacy Officer, Chief Information Security Officer, Data Privacy Program Owner, Application Owners and Assurance Heads that are involved in ensuring data privacy, as part of larger compliance towards data protection regulations.
- Ease of learning and self-service usage, through guided approach of building data management jobs
- In built lean governance around test data provisioning, through metadata management, data dictionary, data privacy reports and visualization, data masking score and trending
- Ability to cater to data privacy needs of heterogeneous business verticals, due to industry-agnostic approach
- Scalability through service-engine based architecture
- User Defined Function Framework for handling niche data processing requirements