How Broadcom Test Data Manager Helps Enterprises Meet Fast-Changing Global Data Security and Privacy Requirements

Between 2009 and 2023, there were 5,887 healthcare data breaches of 500 or more records. These breaches  have resulted in the exposure or impermissible disclosure of 519,935,970 healthcare records. Yet personally identifiable information (PII) isn’t only leaked during a breach. PII can often be inadvertently found in software development repositories and other data sources.

With the advent of privacy and data security regulations across various geographies, organizations are now legally compelled to mask (remove) PII from their data. For example, in addition to the European Union’s General Data Protection Regulation (GDPR), today there are 18+ countries with GDPR-like data privacy laws, including Singapore, Canada, Kenya, South Africa, Australia, and Egypt. While the United States does not have a federal data privacy law, individual states increasingly are passing their own laws. Most recently, Nebraska, Vermont, and Maryland are the latest states to pass data privacy regulations.

To help its global customers better scan, mask, and audit their PII data and meet other compliance requirements, Broadcom introduced the latest version of Test Data Manager earlier this year. This release features close to 40 enhancements to improve performance, usability, and functionality.

Test Data Manager 4.1.1 benefits

Test Data Manager enables users to quickly locate, secure, design, create, and provision ”fit for purpose” test data for the efficient, cost-effective test cycles needed to deliver applications faster. Test Data Manager can also enhance the quality of production data by filling gaps in test data coverage, creating all the data needed to fully cover continuous testing requirements. Following are some of the top benefits in the latest version of this product:

• Unified PII scan: Test Data Manager provides a unified workflow for PII scanning, masking, and auditing, ensuring compliance and simplifying the process. This functionality helps cater to requirements for data privacy, data security, and compliance with regulations like GDPR. Your users can generate a heat map that shows your organization’s PII data. You can then store all these audit results, or you can remediate them by masking the data, and then run the audit again to ensure compliance. Test Data Manager enables you to demonstrate continuous compliance with data privacy regulations.
• Scalable masking: Test Data Manager offers scalable masking capabilities, enabling the fast and efficient masking of large volumes of data. Scalable masking is about the ability to handle large volumes of data in enterprises and provide them to engineering teams at low cost and with no administrative or configuration overhead. In Test Data Manager 4.1.1, we can deploy masking jobs on a Kubernetes infrastructure, and, depending upon the volume of the data, the infrastructure can scale in and scale out in terms of the masking jobs. Customers just need to point to the data that needs to be masked, and we can automatically figure out the number of masking parts that are needed, bring them up, perform the masking actions, as well as bring those parts down when the job is completed.
• NoSQL support:  Test Data Manager now supports NoSQL databases, such as MongoDB, Cassandra, and BigQuery. Recently we have seen an explosion in the number of NoSQL data platforms being used by our customers. Customers use these NoSQL databases as essentially data lakes wherein they are getting data from a multitude of data sources. This comprehensive support includes performance optimizations and compatibility with database-specific data types.

Test Data Manager 4.1.1 also provides other key benefits that contribute to improved data management, compliance, and efficiency in the testing process, including:

• Enhanced usability: The user interface of Test Data Manager has been revamped, moving from AngularJS to ReactJS. This improves usability and compliance with VPAT standards.
• Cloning of FNR models: Test Data Manager allows for the cloning of find and reserve (FNR) models, enabling teams to reuse and modify existing models for their own find and reserve operations.
• Single sign-on authentication: Test Data Manager supports single sign-on authentication using SAML. It can integrate with multiple identity providers, including Okta and Bing.

Using Test Data Manager to build better (and more secure) LLM data models

Today’s enterprises have invested significantly in data science teams, who have been tasked with building data models to make better business decisions. These data fields, which require huge amounts of data, need to be secure and inexpensive. It’s critical to have production data that is sanitized to be fed into these models.

There are data privacy regulations that require organizations to audit the data that goes into large language models (LLMs). Once the data goes into LLMs, it becomes a black box and it is very hard to track where the data came in, which is why it is so critical to scan, mask, and audit PII data before it goes into the model. Test Data Manager’s scalable masking capability can scrub PII information from the data to feed into LLMs.  

Migrating to Test Data Manager 4.1.1

Test Data Manager 4.1.1 enables businesses to meet numerous data privacy and security requirements, while also enabling better, faster decision making using LLMs. To learn more, visit the Test Data Manager page. Not sure whether you are ready to migrate to the latest version or need assistance?  We can provide the information you need to help you migrate in the way that works best for your business.