Difference Between Data Processing Agreement (DPA) and Data Sharing Agreement (DSA)

In the age of big data, businesses frequently handle sensitive information that requires strict governance to protect privacy and ensure compliance with regulatory frameworks. Among the tools that organizations rely on to manage data responsibly are Data Processing Agreements (DPAs) and Data Sharing Agreements (DSAs).

While these agreements may sound similar, they address very different aspects of data handling. Misunderstanding their purposes and applications can lead to compliance failures and reputational risks.

This blog aims to provide a comprehensive guide to understanding the differences, key elements, and applications of DPAs and DSAs.

What is a Data Processing Agreement (DPA)?

A Data Processing Agreement is a legally mandated contract between a data controller and a data processor, ensuring that personal data is processed securely and in compliance with data protection laws, such as the General Data Protection Regulation (GDPR) or similar frameworks worldwide.

Who Are the Parties Involved?

• Data Controller: The organization or individual that determines the purposes and means of processing personal data.
• Data Processor: The entity that processes personal data on behalf of the controller.

Purpose of a DPA

The primary objective of a DPA is to define the responsibilities of both parties involved in processing personal data. This ensures the protection of individuals' data rights and mitigates the risk of misuse or unauthorized access.

Core Elements of a DPA

1. Data Processing Scope: Specifies the type of data, the nature of the processing, and the purpose behind it.
2. Roles and Responsibilities: Clearly outlines the obligations of both the controller and processor.
3. Data Protection Measures: Lists the technical and organizational safeguards implemented to protect the data.
4. Use of Sub-processors: Establishes rules for engaging sub-processors, including the need for approval from the controller.
5. Data Breach Notification: Details the timeline and method for notifying the controller in the event of a data breach.
6. Data Deletion or Return: Defines how data will be returned or deleted after the processing ends.
7. Audits and Compliance: Grants the controller rights to audit the processor’s data handling practices.

When Is a DPA Required?

A DPA is mandatory when:

• An organization outsources data processing activities, such as payroll management, cloud storage, or customer relationship management (CRM).
• A controller shares personal data with a processor for specific tasks, and the processing falls under regulatory oversight like GDPR or CCPA.

What is a Data Sharing Agreement (DSA)?

Unlike a DPA, a Data Sharing Agreement governs the transfer of data between two or more data controllers or entities. Its goal is to ensure that the shared data is used responsibly and in compliance with applicable legal frameworks.

Who Are the Parties Involved?

Data Controllers or Organizations: Typically, entities that independently determine how the data is used, often for mutual benefit or collaboration.

Purpose of a DSA

The main aim of a DSA is to provide clarity and accountability when sharing data, ensuring that all parties understand their roles and agree to abide by legal and ethical standards.

Core Elements of a DSA

1. Purpose of Data Sharing: Clearly defines the reasons for sharing data, such as research, marketing, or joint initiatives.
2. Legal Basis: Establishes the legal justification for data sharing, such as consent, contractual necessity, or legitimate interest.
3. Data Categories: Specifies the type and sensitivity of the data being shared (e.g., personal, anonymized, or aggregated data).
4. Retention Periods: Outlines how long the data will be retained and the criteria for its deletion.
5. Security and Confidentiality: Describes measures to ensure data remains protected during transfer and usage.
6. Data Subject Rights: Ensures that shared data respects the rights of individuals, such as the right to access or delete their data.
7. Termination Provisions: Specifies conditions under which the agreement ends and how the data must be handled post-termination.

When Is a DSA Required?

A DSA is often used in scenarios such as:

• Research collaborations between academic institutions.
• Government bodies sharing data for public policy development.
• Businesses sharing customer data for targeted marketing campaigns or analytics

Key Differences Between DPA and DSA

Real scenarios:

Data Processing Agreement Example

A fintech company contracts a third-party payment gateway to process customer transactions. The DPA ensures that the payment processor handles the personal data securely, notifies the fintech company in case of breaches, and complies with GDPR standards.

Data Sharing Agreement Example

Two pharmaceutical companies collaborate on a drug development project, sharing anonymized patient data from clinical trials. The DSA governs how this data is shared, ensuring it is used only for the stated purpose and remains confidential.

Common Mistakes and Best Practices in Using DPAs and DSAs

Managing data responsibly through agreements like DPAs and DSAs is crucial for organizations. However, errors in drafting, implementing, or maintaining these agreements can lead to non-compliance, financial penalties, and reputational harm.

Mistakes to Avoid

• Confusing Terms: Misinterpreting the Difference Between a DPA and DSA
  • The Mistake: Many organizations mistakenly use a DPA when a DSA is required, or vice versa. For example, treating a data-sharing scenario as a data-processing relationship could result in inadequate safeguards for the shared data or overlooked obligations.
  • The Impact: Misclassification can lead to legal non-compliance, especially under regulations like GDPR, where DPAs are mandatory, while DSAs, though recommended, may not be. This confusion can expose organizations to data misuse risks or regulatory scrutiny.
  • Example: A company sharing customer data with a research firm may use a DPA instead of a DSA, neglecting to outline shared responsibilities and compliance requirements for data use.

• Incomplete Agreements: Failing to Address Data Security or Breach Protocols
  • The Mistake: Overlooking essential elements such as data security measures, data breach response protocols, or the roles of sub-processors.
  • The Impact: Incomplete agreements leave gaps that can be exploited, leading to data breaches, fines, and reputational damage. Additionally, the lack of clear guidelines during a breach can result in delayed responses, exacerbating the damage.
  • Example: A DPA that fails to specify encryption standards or the processor’s obligation to notify the controller within 72 hours of a breach may cause severe non-compliance issues under GDPR.

• Not Updating Agreements: Neglecting Periodic Reviews
  • The Mistake: Treating these agreements as static documents rather than dynamic ones that need regular updates.
  • The Impact: Regulations, technologies, and business processes evolve, rendering outdated agreements ineffective or non-compliant.
  • Example: A company using a DPA drafted pre-GDPR may not align with modern requirements, like addressing cross-border data transfers, leaving the organization vulnerable to legal and operational risks.

Best Practices

• Customize Agreements to Reflect the Specific Data and Relationship
  • Why It’s Important: Each data-processing or data-sharing relationship is unique, with varying types of data, purposes, and regulatory requirements. A one-size-fits-all approach doesn’t work.
  •  How to Implement:
    • Identify the type of data involved (e.g., personal, sensitive, anonymized).
    • Clearly define the relationship between parties—controller and processor for a DPA or controller-to-controller for a DSA.
    • Customize clauses to reflect industry standards, regulatory demands, and the nature of the partnership.
  • Example: A healthcare provider sharing anonymized patient data with a research institute should include clauses in the DSA about ethical data usage and IRB (Institutional Review Board) compliance.

• Involve Legal Experts to Draft and Review Agreements
  • Why It’s Important: Privacy laws and data protection regulations are complex and vary across jurisdictions. Legal experts ensure agreements meet the necessary legal and operational requirements.
  • How to Implement:
    • Consult legal counsel during the drafting stage.
    • Periodically review agreements with a legal expert, especially after regulatory updates like GDPR revisions or new regional laws like California’s CCPA.
  • Example: A multinational company may require expertise to address cross-border data transfer clauses in a DPA, ensuring compliance with GDPR, CCPA, and other applicable regulations.

• Clearly Communicate Terms and Obligations
  • Why It’s Important: Agreements are only effective if all involved parties understand their roles, responsibilities, and compliance requirements. Lack of awareness can lead to unintentional violations.
  • How to Implement:
    • Provide training sessions for internal teams and external partners.
    • Distribute a summary of key terms and responsibilities to stakeholders.
    • Include clear points of contact for questions or clarifications.
  • Example: A SaaS provider working with multiple sub-processors can minimize errors by providing processors with a guide to the DPA’s obligations, such as data encryption standards and breach notification timelines.

• Periodically Audit Compliance with the Terms of the Agreement
  • Why It’s Important: Regular audits identify gaps, ensure compliance, and build trust between parties. They also provide documentation to regulators in case of an investigation.
  • How to Implement:
    • Schedule periodic internal and external audits.
    • Use automated compliance tools to monitor adherence to security protocols.
    • Document audit results and address any identified issues promptly.‍
  • Example: A company using a DPA with a cloud service provider can conduct quarterly audits to ensure data storage and access protocols meet GDPR standards.

Conclusion

Data Processing Agreements and Data Sharing Agreements are vital instruments in managing data responsibly. While a DPA focuses on safeguarding data during processing, a DSA ensures proper governance when data is shared between entities.

Understanding and implementing DPAs and DSAs effectively requires attention to detail and proactive management. Avoiding common mistakes like confusing terms, overlooking crucial elements, or failing to update agreements is as important as adopting best practices like customizing agreements, seeking legal counsel, ensuring stakeholder awareness, and conducting regular audits.

By prioritizing these measures, organizations can not only ensure regulatory compliance but also foster a culture of trust and responsibility around data management. Whether you’re a data controller, processor, or collaborator, these steps will help you manage data confidently in an increasingly complex regulatory landscape.