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Client
A global healthcare company
Industry
Healthcare
Services
Security Services
Tech
Databases, SalesForce, Informatica Cloud, Informatica TDM, Python

Challenge

In the wake of data privacy laws, data loss prevention was a big concern for a global healthcare company with complex IT infrastructure needs. They were looking for a top provider of data masking services to obfuscate huge volumes of personally identifiable information (PII) in multiple formats sitting in both production and non-production environments. The company needed a complete healthcare solution to comply with their internal controls, the GDPR and other data privacy legislation.

Specifically, our team took on the following challenges:
●
Provide Data Masking as a Service to protect sensitive data in the client’s complex ecosystem consisting of relational databases, cloud apps and unstructured sources
●
Create an ML-driven solution to find and mask PII for the staging/development environments

Solution

●
A turnkey process performing data masking operations on demand to meet development and testing needs across the enterprise
●
A custom Python app using an ML model for processing data sources upon request, providing a list of sensitivity attributes, such as the level of sensitivity and the PII type, and suggesting an appropriate masking technique based on the identified attributes
●
A data masking framework based on Informatica TDM that performs anonymization procedures
●
A Python bootstrap application for masking SalesForce data by automatically generating jobs in Informatica Cloud
●
Rules for sensitive data identification
●
Data dictionaries that can be used for data substitution
ML-Driven Solution for Healthcare
healthsecurity

Impact

●
With sensitive data shielded from unauthorized access, the company has quickly achieved compliance with the GDPR and other data privacy laws
●
The automated provisioning of masked data to developers and testers has dramatically cut time to create non-production environments
●
Millions of rows of data, including structured, semi-structured and unstructured data, are processed swiftly, driving process efficiency
●
Costs on Salesforce data transfer from production to sandbox have lowered

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