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In the 21st century, customer data is one of the most coveted possessions. The successful commoditization of end-user’s data had led to the exponential growth of the five best performing American technology companies (FAANG+). This initiated the rat race of data collection and fueled the need for data privacy and protection. Stringent data regulations were formulated like the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA). They brought a tectonic shift in data protection, from being ‘good-to-have’ guidelines to ‘must-have’ mandates. However, these guidelines posed a sudden challenge towards adherence. After thorough contemplation, data anonymization was identified as one of the most trusted and recognized industry solutions. It is a process of identifying personal details and replacing them with fictitious, but realistic values that preserve data utility. The next big hurdle was the implementation of anonymization across the enterprise.
Implementing Data Anonymization – Challenges
The key challenges can be categorized as follows:
Five Phased Methodology for Data Anonymization
Being a niche and new area, data anonymization should follow a phased approach for enterprise-wide implementation. TCS suggests a ‘Five Phased Methodology’ depicted as follows:
Figure 1: Five Phased Methodology for Data Anonymization
Preparation Phase
The owner of the data privacy program initiates the project. The scope is derived by assessing applications in the IT landscape. Data privacy regulatory compliance is the key driver for the requirements list.
The key activities are:
Analysis Phase
The implementation team follows the data privacy definition and work scope to perform the due diligence.
The key activities are:
Configuration Phase
Data privacy implementation is a unique exercise for each enterprise. After data anonymization strategy is verified, rules are configured using the selected anonymization product.
(Tip: A good data anonymization product should provide an automated and easy-to-use graphical interface for configuring the anonymization rules using built-in templates.)
The key activities are:
Execution Phase
After data anonymization configuration is ready and verified, it is time for execution.
The key activities are:
Validation Phase
Data validation is a mandatory step for checking sanctity of the masked target data environment – both for integrity of business rules and protection of personal details.
The key activities are:
Data Privacy Governance
A system is bound to fall apart in the absence of good governance, despite a strong design. An established governance system ensures continuity of usual operations and continuous enhancements to keep the system relevant. Data privacy governance constitutes of the following components:
Figure 2: Data Provisioning Process
A centralized test data management team is preferred for implementing the data provisioning process, while the governing body ensures discipline through the set processes and usage of the tools.
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