Data compliance is a set of practices and controls that are implemented to ensure data is treated in alignment with laws, regulations, policies, and standards. 

It typically refers to the collection, processing, organization, and management of data assets within an organization. Local compliance laws may mandate what processes need to be in place for the data to be protected.

Adhering to data compliance best practices helps to maintain the confidentiality, integrity, and availability of sensitive or personal data, such as customer details or personally identifiable information (PII). This can help to prevent data misuse, theft, and loss.

Different geographies and industries are subject to varying compliance standards, such as:

  • The General Data Protection Regulation (GDPR) in Europe.
  • Health Insurance Portability and Accountability Act (HIPAA) for healthcare in the United States.
  • The California Consumer Privacy Act (CCPA) in California, United States. 

These governance frameworks all share similar goals relating to data storage and protection.

Why is data compliance important? 

Widespread adoption of cloud and other digital services — for example, AI models — has increased scrutiny of how data is collected and processed. This is driven by the global growth of user-generated data. 

Organizations that follow data compliance practices are better equipped to create internal data handling policies that are aligned with industry regulations like GDPR or HIPAA. Compliance policies that encompass security and privacy measures can prevent data misuse or loss in a breach. In 2024, the average cost of a data breach was $4.88 million, a 10% increase compared to 2023. 

Data is regularly transferred internationally and may include publicly available data. This is particularly relevant in the context of generative AI, including large language models (LLMs).

Compliance enables stakeholders to protect user data and privacy, and trust the quality of their data. This is highly valuable when using AI to support data-driven decision-making such as financial forecasting or patient data analysis. 

Why do organizations need data compliance?

Regulating data and its use has become a central focus of many laws and industry standards — for example, the Sarbanes-Oxley Act (SOX) in finance or HIPAA in healthcare.

Data compliance is especially relevant thanks to widespread adoption of AI and global data transfers. It helps organizations manage data effectively and in line with regulations. Regular compliance audits can ensure that systems remain secure and effective.

Failure to adequately protect the integrity of data and meet compliance obligations can lead to negative consequences, such as data breaches, fines, or reputational damage. 

What are the key principles of data compliance?

Key principles in data compliance provide organizations with a clear framework to follow. This ensures data is managed securely and in accordance with local laws and regulations.

Data minimization

Data minimization refers to only retaining data that is useful or relevant for a particular task. This limits the amount of data that organizations collect and focuses on using necessary data for a specific purpose. In AI models, this means only using the minimum data required to generate outputs.

Data integrity and confidentiality

Data must be accurate, reliable, and protected from unauthorized access and modifications. This ensures data is high quality, which improves AI model performance.

Data compliance provides organizations with the appropriate measures to preserve data integrity and confidentiality. This includes anonymizing data to reduce the risk of harm in a data breach.

Data fairness and transparency

Collected data should be processed lawfully, fairly, and transparently. This includes creating clear data processing policies which support explainability requirements in compliance frameworks. These typically inform customers or users how their data is collected, used, and shared. 

Storage limitation

Data should be stored for the shortest possible time. Redundant or irrelevant data should be anonymized or deleted once it has fulfilled its business or legal purpose.

Accountability

Regular audits and maintenance of data access records can hold organizations accountable for how the data is handled. This includes creating internal policies governing data processing that support data compliance efforts. Accountability for data processing typically forms part of data compliance frameworks — for example, GDPR — by providing audit trails.

Data compliance across industries

Different industries each have their own set of data compliance rules and standards, affecting how organizations use customer or user data.

Finance

Financial institutions are subject to specific regulations aimed at safeguarding payment card data and ensuring accurate financial reporting. Key regulations include:

  • Payment Card Industry Data Security Standards (PCI DSS): Applicable to all businesses that handle cardholder data, including third-party providers. This is a contractual obligation covering the acceptance, storage, and transfer of cardholder information.
  • The Sarbanes-Oxley Act (SOX): U.S. legislation that promotes transparency and accountability in financial reporting and governance. It applies to publicly traded organizations and requires the implementation of strict internal controls to ensure financial data integrity. Non-compliance may result in fines and penalties.

Healthcare

Healthcare organizations in the United States must comply with regulations designed to protect personal health information (PHI).

The Health Insurance Portability and Accountability Act (HIPAA) sets standards for managing patient PHI with a focus on confidentiality and security. Compliance is required not only for healthcare providers but also for associated entities. 

These include insurance providers that handle patient coverage, data transmission services that manage electronic health data, and medical transcription services that convert clinical notes into digital records.

Retail

Retail organizations must follow privacy regulations that focus on personal data protection and consumer rights.

The General Data Protection Regulation (GDPR), governed by the European Union, gives consumers control over how their personal information is collected and used. It applies to organizations both within and outside of Europe. 

Under GDPR, retailers must clearly explain how they collect data and ensure transparency in their methods. They are also required to obtain explicit consent from consumers before collecting or processing personal data, such as marketing preferences.

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