SQL Template for Managing GDPR-Sensitive Data in Databases

Managing GDPR-sensitive data requires marking fields, ensuring proper retention, and setting up automated deletion processes. Below is an extended SQL template with typical fields that could exist in a database, helping you build in Security by Design and GDPR compliance from the start.

SQL Template for GDPR Compliance:

sql

-- Main User Table with Various GDPR-Sensitive Fields
CREATE TABLE users (
    user_id INT PRIMARY KEY,
    email VARCHAR(255) COMMENT 'GDPR: Contains PII',
    full_name VARCHAR(255) COMMENT 'GDPR: Personally identifiable information',
    birthdate DATE COMMENT 'GDPR: Sensitive personal data',
    phone_number VARCHAR(20) COMMENT 'GDPR: Contact information',
    address VARCHAR(255) COMMENT 'GDPR: Home address, personal data',
    national_id VARCHAR(50) COMMENT 'GDPR: National identification number',
    credit_card_number VARCHAR(20) COMMENT 'GDPR: Financial data',
    account_creation_date DATE COMMENT 'Retention: Store for 5 years under financial laws',
    last_login_date DATE COMMENT 'GDPR: Tracks user activity, delete after 2 years of inactivity',
    ip_address VARCHAR(45) COMMENT 'GDPR: IP address, can be considered personal data',
    preferences JSON COMMENT 'GDPR: User preferences, potentially containing PII',
    marketing_consent BOOLEAN COMMENT 'GDPR: Tracks user consent for marketing',
    account_status VARCHAR(50) COMMENT 'GDPR: Data related to account, may impact deletion rules',
    deletion_request_date DATE COMMENT 'GDPR: Date of deletion request, if applicable'
);

-- Transaction Table to Handle Financial Data
CREATE TABLE transactions (
    transaction_id INT PRIMARY KEY,
    user_id INT COMMENT 'GDPR: Links to personal user data',
    transaction_date DATE COMMENT 'GDPR: Retain for 5 years under financial laws',
    transaction_amount DECIMAL(10, 2) COMMENT 'GDPR: Financial data',
    payment_method VARCHAR(50) COMMENT 'GDPR: Payment information',
    card_last_four_digits VARCHAR(4) COMMENT 'GDPR: Partial credit card data',
    billing_address VARCHAR(255) COMMENT 'GDPR: Billing details, personal data',
    FOREIGN KEY (user_id) REFERENCES users(user_id)
);

-- Metadata Table to Track Sensitive Data and Retention
CREATE TABLE field_metadata (
    table_name VARCHAR(255),
    field_name VARCHAR(255),
    gdpr_relevant BOOLEAN,
    retention_period INT COMMENT 'Retention period in years (if applicable)',
    sensitive_type VARCHAR(255) COMMENT 'e.g., PII, financial data, contact information'
);

-- Example Metadata Entries for GDPR-Relevant Fields
INSERT INTO field_metadata (table_name, field_name, gdpr_relevant, retention_period, sensitive_type)
VALUES 
('users', 'email', TRUE, NULL, 'PII'),
('users', 'full_name', TRUE, NULL, 'PII'),
('users', 'birthdate', TRUE, NULL, 'Sensitive personal data'),
('users', 'national_id', TRUE, NULL, 'National identification number'),
('users', 'credit_card_number', TRUE, NULL, 'Financial data'),
('transactions', 'transaction_date', FALSE, 5, 'Financial data'),
('transactions', 'payment_method', TRUE, NULL, 'Payment information'),
('users', 'last_login_date', TRUE, 2, 'User activity data'),
('users', 'deletion_request_date', TRUE, NULL, 'Data related to GDPR request');

Key Points:

• Retention Management: Fields like transaction_date are stored for a specific period (e.g., 5 years) to comply with financial retention laws, while others like last_login_date can be deleted after a period of inactivity.
• Automated Deletion/Anonymization: When a user requests deletion, fields marked as GDPR-relevant can be removed or anonymized while legally retained data remains intact.
• Sensitive Data Types: Identifying different types of sensitive data (e.g., PII, financial data) ensures that they are handled correctly and in compliance with GDPR.

This template can be adapted to suit various business requirements, helping you implement a secure and GDPR-compliant database design.

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