CCPA: Understanding how synthetic data can help achieve compliance

You’ve probably felt the pain of trying to move fast while navigating a growing maze of privacy rules. Data compliance is often framed as a legal checklist—but in reality, it’s a systems challenge that plays out in your codebase, CI/CD workflows, and staging environments. How do you ensure privacy protections are embedded directly into the software development lifecycle?

The California Consumer Privacy Act (CCPA), enacted in 2018 and enforced since 2020, gives California residents more control over their personal information. CPRA, which came into effect in 2023, strengthens those protections further. Yet despite years of runway, only 11% of U.S. businesses are fully compliant.

You and your team can close that gap by building compliance into your infrastructure through CCPA compliance software and safe test data generation.

What is the CCPA?

The California Consumer Privacy Act (CCPA) gives residents of California control over how their personal data is collected, used, and sold. It was designed to address rising concerns around data privacy, especially in the context of digital platforms and targeted advertising. Its key tenets include:

• Right to Know: You must give users access to a record of the personal data you've collected about them and explain how it's being used.
  
• Right to Delete: Consumers can ask you to delete their personal data, and you must comply with certain exceptions.
  
• Right to Opt-Out: Users can opt out of having their data sold to third parties.
  
• Right to Non-Discrimination: You can’t penalize users for exercising their privacy rights.

The added impact of the CPRA

The CPRA, which amends and extends the CCPA, went into effect in January 2023. It introduces new requirements for handling “sensitive personal information,” mandates stricter data minimization and storage limitation practices, and expands user rights, including the right to correct inaccurate data.

To meet CPRA requirements, you’ll need to configure a broad range of systems—from frontend interfaces to backend services, APIs, logs, and test environments—to recognize and enforce new categories of user rights and data constraints.

Who needs to comply with CCPA

If your organization does business in California and meets one or more of the following criteria, you're likely subject to CCPA/CPRA:

• Annual gross revenue over $25 million
  
• Buy, receive, sell, or share personal data of 100,000 or more consumers or households
  
• Earn more than 50% of annual revenue from selling personal data

Even if you’re not headquartered in California, you’re still on the hook if you collect data from California residents. And it’s not just production environments—if your dev or QA teams are using real customer data in non-production systems, you could be violating CCPA without realizing it.

How to comply with CCPA

To comply with CCPA, you’ll need to integrate a combination of monitoring tools, consent systems, and modern CCPA compliance software, including synthetic data solutions, to build privacy protections directly into your dev workflows. Here's how to engineer compliance into your stack:

Consent management platform

You need to respect user preferences at every point of interaction. A consent management platform (CMP) helps collect, store, and synchronize those preferences across systems. Look for CMPs with API integrations so you can programmatically update user consent states and enforce them downstream.

Handling sensitive data

Under CPRA, sensitive personal information includes race, religion, health data, precise geolocation, and more. These values often slip into logs, support tickets, and shadow databases. Make sure your architecture includes classification tools and field-level controls to flag and segment sensitive data from general PII.

If you find you need to protect data in unstructured sources like logs or user-submitted text, CCPA compliance software like Tonic Textual enables automated detection and de-identification of sensitive information, helping you ensure that even free-form data is safe to use in downstream systems. This reduces manual data scrubbing and helps you maintain CCPA standards without slowing development.

Data processing

CCPA requires you to maintain auditability—who accessed what, when, and why. That means adding logging, immutable audit trails, and scoped permissions throughout your data pipeline. Use ephemeral environments and infrastructure-as-code to reduce long-lived data exposure, especially in dev/test. Invest in CCPA compliance software like Tonic Ephemeral to provision fully hydrated test databases in seconds, so you can reduce long-lived data exposure in CI/CD workflows.

Privacy management tools

Privacy tools can help detect PII, enforce retention policies, and trigger alerts when sensitive data shows up where it shouldn't. These tools should plug into your existing stack—data warehouses, observability platforms, version control—and support real-time scanning and remediation.

Synthetic data

Synthetic data replaces real data with statistically similar, privacy-preserving values that can be used safely in dev, test, and AI training without risking re-identification.

CCPA compliance software solutions like Tonic Structural, Tonic Textual, and Tonic Fabricate generate high-fidelity synthetic datasets that integrate into your CI/CD pipelines, helping you ship faster while staying compliant, without relying on brittle masking scripts or manual workflows. 

Conclusion

CCPA compliance isn’t just a legal checkbox. It’s an engineering discipline. You can’t bolt on privacy at the end of the build; it needs to be part of how you design, deploy, and iterate.

By embedding privacy-first practices like real-time consent enforcement, data lineage tracking, and synthetic data, you can turn compliance from a blocker into a catalyst for better software.

Want to see how compliance fits cleanly into your developer workflows? Book a demo today.