Why privacy automation is the only route to CCPA de-identification compliance

by | Oct 29, 2019 | CCPA, Data Privacy Solutions, Data Privacy Technology, Data Science, Privacy blog

The volume and variety of big data is surpassing the functionality of traditional privacy management. With the California Consumer Privacy Act (CCPA) coming into effect on January 1, 2020, it is more critical than ever for every organization operating in California to make real changes in how they manage their data. The only viable solution is privacy automation.

Traditional data privacy management approaches are slow, unscalable, and imperfect

Across organizations, data drives results. Yet the velocity at which data is growing threatens to turn this “new oil” from a profit-driver to fine-magnifier. 

Organizations are continuously collecting data in massive volumes, while data consumers utilize that information to perform their day to day jobs. This ceaseless cycle of data acquisition and analysis makes it almost impossible for organizations to monitor and manage all their data.

Yet today, data privacy management is often performed manually, with a survey-based approach. These processes do not scale. Not only are they unreliable, but manual implementation slows down data analysis and has made it impossible to stay current with privacy regulations. On top of this, first-generation techniques such as encryption, masking and hashing no longer cut it. In consequence, privacy and compliance teams are seen to be preventing companies from unlocking their most valuable resource. 

In reality, compliance is impossible with manual human review. It would be like cutting your lawn with a pair of scissors. 

Privacy compliance requires a unified effort from the various departments and privacy-related stakeholders within an organization. This requires the right tools and processes.

Now, with the CCPA coming into effect on January 1, 2020, organizations are being put to the test. For the first time, enterprises with operations in California will be held accountable to strict privacy regulations. There is an urgent need to build a manageable and effective data privacy strategy.

Under the CCPA, personal data cannot be used for secondary purposes unless explicit notice and the opportunity to opt-out has been provided from each user. These secondary purposes, like data science and monetization, are what makes data so valuable – why risk opt-outs?

If data has been de-identified or aggregated, it is no longer restricted. However, the standards for data classification as “de-identified or aggregated” are extremely high, and traditional methods of anonymization, like tokenization and hashing, will not cut it. It is only when advanced privacy techniques (differential privacy, k-anonymization) are applied correctly that data science and monetization can continue.

As a result, the complex structures of the average organization require a single enterprise-wide, end-to-end, automated solution to meet data and privacy compliance regulations: Privacy Automation.

 

Privacy automation: the only tool that can ensure CCPA compliance

Privacy automation assesses, quantifies and assures privacy by measuring the risk of identification, applying privacy-protection techniques, and providing audit reports throughout the whole process. With AI and a combination of the most advanced privacy techniques, this solution will simplify the compliance process and allow for privacy rules definition, risk assessments, application of privacy actions, and compliance reporting to happen within a single application. This process is part of what is known as Privacy by Design and Privacy by Default.

With Privacy Automation, metadata classification becomes possible. This lets you generate an automated and easy-to-understand privacy risk score.

Automation extends enterprise-wide, harmonizing the needs of Risk and Compliance and data science teams, and ensuring regulations are abided. This allows companies to unlock data in a manner that protects and adds value to consumers in a safer method than manual privacy-protection.

With privacy automation, enterprises can leverage state-of-the-art solutions to innovate without limitation or fear. In consequence, it is the only tool that will realistically enable enterprises to become CCPA-compliant by January 2020.

For more information, read our blog, The Business Incentives to Automate Privacy Compliance Under CCPA.

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