Idea | Description | Jira | |
---|---|---|---|
1 | AI-driven sensitive search algorithms. | Achieve comprehensive categorization and search capabilities for sensitive data using external AI integration. Increase result quality with a fully automated and streamlined process, enhancing the accuracy and efficiency of sensitive data masking rules assignment. | |
2 | Complex masking rules with dependencies |
Consider relationships and dependencies between different columns. With the introduction of calculated field rules, our service will be significantly enhanced, enabling it to handle more complex data dependencies and correlations | |
3 | AI-driven masking data dictionary generators | Effortlessly generate masking lookup tables content using AI technology, significantly reducing the time required for creating masking rules. | |
4 | Sensitive data search scan specific tables only | help users to narrow down the scope of their sensitive data scans to specific user-specified data schemas and tables. Reasons: debugging, interested in the selected tables only, quicker delivery of updated rules due to reducing time, breaking down lengthy scanning process into manageable parts, enhancing user control. | |
5 | Free-text masking rules | Enhance the process of masking sensitive information in free text by incorporating NLP techniques to understand, interpret, and manipulate the free text data. Recognize patterns that indicate the presence of sensitive data and generate masked values preserving the same format and structure as the original data. | |
6 | Masking licensing with size limitations | Implement a licensing mechanism that limits customer's operations based on the total size of all their database sources. The license key will be associated with a size limitation. This approach allows Accelario to offer tiered pricing plans based on database sizes | |
7 | Integration with Virtualization | Unifying the Masking service with Virtualization within the single TDM platform. | |
8 | Integration with development tools | Enhancing collaboration with CI/CD tools, offering a API toolbox or SDK for easier integration. | |
9 | Read-only environments for the Masking | Read-only environments that can be safely utilized for production databases. | |
10 | Read-only test masking | Implementing in-memory read-only masking for efficient and secure fast masking results during the masking development phase. | |
11 | Masking reconciliation | Ensure the accuracy and consistency of masked data by automatically comparing and validating the masked values against their original records. | |
12 | Scheduling of masking jobs | Enhancing the process, scheduling, and reporting of background masking jobs, including email notifications for results. |
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