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Retail Case Study

Internal Privacy Policy & FDA Regulations

Company Overview

Multi-billion dollar, global chain of department and warehouse stores, with over one million employees.

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Business Problem

A major global retailer needed to protect the identities of their many employees, primarily their Social Security Numbers (SSN), according to internal privacy policies.

This meant applying protection capabilities in the Teradata IDW, as well as Pivotal HD and SQL Server.

Subsequent drivers included protecting the identities of their customers to enable secure analytical and operational processes according to the US Food & Drug Administration (FDA) reporting requirements.

Requirements and Challenges

Protect SSN of employees in Teradata IDW
Protect private customer data in Pivotal HD & SQL Server according to FDA OTC drug reporting requirements
Enable security scalability and expansion to new business systems

Character preservation through the entire data flow – FTP, Hadoop (Hive), DataStage, Teradata, User application
Scripts and Coding Alignment – maintain consistency between production and dev-test environment
Future Proof – Support for other European character sets, new data sources
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Protegrity Solution

Fine-grained data tokenization was applied to key data elements that allowed the IT team to leverage the data in a protected form. The test environment remains full-functioning but unauthorized users are unable to access or grant access rights to sensitive data in the clear.

Critical to the success of the solution, Protegrity also enabled the CISO to determine and specify what data is to be protected, where it is to be enforced, who will have access and when and how the data will be protected.

Enterprise key management (EKM) capabilities are integrated into the platform and provide an easy-to-use system for managing keys. Built-in comprehensive auditing and reporting provides the insight needed to track usage and patterns.

Results & Benefits

Met or exceeded all requirements in the internal privacy policy
Protegrity Vaultless Tokenization preserved data structure and column widths
Audited compliance to new data security policy
Negligible changes to functional processes using de-identified data
Implemented fine-grained data security on any/all character sets and data sources, without significant changes to CDW
Clear separation of duties implemented with the data security policy