Technological Tools That Simplify the DSAR Process

The Data Subject Access Request (DSAR) is a critical aspect of data protection laws worldwide, especially under regulations like the General Data Protection Regulation (GDPR) in the European Union and the Data Protection Act 2018 in the UK. A DSAR is a formal request made by an individual to obtain access to their personal data that an organisation holds. Under these laws, organisations are required to respond to these requests in a timely and transparent manner. However, the DSAR process can be complex, time-consuming, and resource-intensive, particularly for large organisations with vast amounts of data.

Technological advancements have emerged as vital tools to help organisations handle DSARs efficiently, reducing manual effort, enhancing compliance, and minimising risks. This article explores the technological tools that are simplifying the DSAR process and the key features that make them indispensable in today’s data-driven landscape.

The Growing Importance of DSARs

With the increase in public awareness of privacy rights, more individuals are exercising their right to request access to their personal data. Organisations, regardless of size, must be prepared to handle these requests promptly. The failure to comply with DSARs can lead to significant fines, not to mention damage to a company’s reputation.

In 2023, the Information Commissioner’s Office (ICO) in the UK reported a 40% increase in DSAR-related complaints compared to previous years. This highlights the growing importance of having a robust DSAR handling process. Moreover, with the rise of artificial intelligence and big data analytics, the volume of personal data collected and processed by organisations has increased exponentially. As such, manual methods of handling DSARs are no longer sufficient, making technology an essential enabler of compliance.

Key Challenges in Handling DSARs

Before delving into the specific technological tools that simplify the DSAR process, it is essential to understand the challenges organisations face:

1. Data Volume and Complexity: Modern organisations store data across various systems, including cloud services, internal servers, and third-party platforms. Locating all the data related to an individual can be a complex and time-consuming process.
2. Data Sensitivity: Personal data often includes sensitive information that must be handled with care. Redacting or anonymising certain portions of data to protect third-party privacy while responding to a DSAR can be challenging.
3. Time Constraints: Under GDPR, organisations have one month to respond to a DSAR. With manual methods, meeting this deadline is difficult, especially when large volumes of data need to be retrieved, reviewed, and redacted.
4. Human Error: Manual processing of DSARs is prone to errors, particularly in large-scale operations where data is fragmented across systems. Missing or incomplete data responses can result in regulatory penalties.
5. Cost: Managing DSARs manually requires significant resources, including personnel, time, and money. As the number of requests grows, so too do the associated costs.

Technological Tools That Simplify the DSAR Process

A wide range of technological tools can streamline the DSAR process, making it more efficient, accurate, and cost-effective. These tools leverage advancements in automation, artificial intelligence, and machine learning to ensure compliance while minimising the burden on internal teams.

DSAR Automation Platforms

Automation is at the heart of modern DSAR solutions. DSAR automation platforms are designed to streamline every aspect of the process, from receiving requests to delivering responses. These platforms offer end-to-end solutions, automating repetitive tasks and reducing the need for manual intervention.

Key Features of DSAR Automation Platforms:

• Request Tracking: These platforms provide a centralised system for tracking and managing DSARs, ensuring that deadlines are met and requests are processed in a timely manner.
• Data Discovery: Automation platforms can integrate with various data sources, including databases, cloud storage, and third-party systems, to automatically locate all personal data associated with a requestor.
• Redaction and Anonymisation: Many platforms offer built-in tools for redacting sensitive information or anonymising data to protect third-party privacy. This helps organisations meet regulatory requirements while safeguarding personal data.
• Audit Trails: Automated platforms maintain a detailed audit trail of the entire DSAR process, providing transparency and accountability for compliance purposes.

Examples of DSAR Automation Platforms:

• OneTrust: OneTrust offers a comprehensive privacy management platform that includes DSAR automation. Its automation capabilities allow organisations to manage requests, automate data discovery, and ensure timely compliance.
• TrustArc: TrustArc provides a privacy management solution that streamlines DSAR workflows, automating tasks like data collection, review, and response generation.
• Securiti.ai: Securiti.ai leverages artificial intelligence to automate the DSAR process. Its platform automatically discovers data across various systems and helps organisations meet compliance obligations with minimal effort.

AI-Powered Data Discovery Tools

One of the most time-consuming aspects of responding to a DSAR is identifying all the personal data held by an organisation. AI-powered data discovery tools use machine learning algorithms to search through vast amounts of structured and unstructured data quickly and accurately.

Key Features of AI-Powered Data Discovery Tools:

• Automated Search: AI tools can automatically search across multiple data sources, including emails, databases, and cloud services, to find all relevant personal data.
• Natural Language Processing (NLP): Advanced AI tools use NLP to understand the context and semantics of data, ensuring that all relevant information is retrieved, even if it’s stored in non-standard formats or across different languages.
• Data Mapping: AI tools create a data map that identifies where personal data is stored and how it flows through different systems. This helps organisations locate data quickly when a DSAR is received.
• Data Classification: AI tools can classify personal data based on sensitivity, helping organisations prioritise which data needs to be redacted or anonymised before responding to a request.

Examples of AI-Powered Data Discovery Tools:

• BigID: BigID uses machine learning to automatically discover, map, and classify personal data across an organisation’s data landscape. This enables organisations to respond to DSARs more efficiently.
• DataGrail: DataGrail integrates with over 100 applications and systems to automate data discovery and provide real-time insights into where personal data is stored.

Data Subject Portals

Many organisations are now implementing self-service portals that allow individuals to submit DSARs directly and track the progress of their request. These data subject portals improve the user experience and reduce the burden on internal teams by providing a streamlined, transparent process.

Key Features of Data Subject Portals:

• User-Friendly Interface: Data subject portals offer an intuitive interface that allows individuals to easily submit DSARs and track the status of their requests in real-time.
• Identity Verification: Portals often include identity verification mechanisms to ensure that the person submitting the request is the rightful data subject. This helps prevent fraudulent DSARs and enhances data security.
• Communication Hub: Portals provide a central hub for communication between the organisation and the data subject, enabling real-time updates and responses to queries.

Examples of Data Subject Portals:

• OneTrust Data Subject Portal: OneTrust’s portal enables individuals to submit, manage, and track DSARs from start to finish. It integrates with the wider OneTrust platform to ensure seamless processing of requests.
• Privitar: Privitar offers a self-service data subject request portal that provides an easy-to-use interface for individuals to exercise their data rights.

Automated Redaction Tools

Handling sensitive data within DSARs often requires redacting certain portions to protect the privacy of third parties or proprietary information. Automated redaction tools simplify this process by using AI to identify and redact sensitive information across various types of documents.

Key Features of Automated Redaction Tools:

• Text and Image Redaction: Automated tools can redact not only text but also images, ensuring that all sensitive data is protected.
• Customisable Redaction Rules: Organisations can set specific rules for redacting certain types of data, such as national insurance numbers, financial information, or health records.
• Batch Processing: Automated redaction tools can process large batches of documents at once, significantly reducing the time it takes to prepare data for DSAR responses.

Examples of Automated Redaction Tools:

• CaseGuard: CaseGuard offers an AI-powered redaction tool that can automatically identify and redact sensitive information in documents, images, and video files.
• Relativity Trace: Relativity Trace uses machine learning to automatically identify sensitive data and apply redactions, speeding up the DSAR response process.

Data Retention and Deletion Tools

While data retention policies are crucial for complying with data protection regulations, they also play an important role in the DSAR process. Organisations need to ensure they are retaining only the data they are legally allowed to keep and that any data outside of retention periods is properly deleted. Data retention and deletion tools help automate these processes.

Key Features of Data Retention and Deletion Tools:

• Automated Deletion: These tools can automatically delete personal data once it reaches the end of its retention period, reducing the amount of data that needs to be processed during a DSAR.
• Policy Enforcement: Organisations can create data retention policies that are automatically enforced, ensuring compliance with GDPR and other regulations.
• Deletion Audits: These tools maintain a log of all data deletions, providing an audit trail that can be useful for demonstrating compliance.

Examples of Data Retention and Deletion Tools:

• Veeam: Veeam offers data retention and deletion tools that automate the process of removing outdated personal data, reducing the amount of information that must be retrieved during a DSAR.
• Commvault: Commvault provides a comprehensive data management solution that includes automated data retention and deletion features.

Collaboration Tools

Responding to a DSAR often requires input from multiple departments, including legal, IT, and compliance teams. Collaboration tools help streamline communication and ensure that everyone involved in the process is working together efficiently.

Key Features of Collaboration Tools:

• Real-Time Collaboration: These tools enable team members to collaborate on documents and workflows in real-time, ensuring that the DSAR response process is as efficient as possible.
• Task Assignment: Organisations can assign specific tasks to different team members, such as data retrieval, redaction, or review, and track the progress of each task.
• Document Sharing: Collaboration tools provide a secure platform for sharing documents and information related to the DSAR response.

Examples of Collaboration Tools:

• Microsoft Teams: Microsoft Teams provides a secure platform for collaboration, enabling teams to work together on DSAR responses in real-time.
• Slack: Slack’s collaboration features allow teams to communicate and share documents securely, helping to streamline the DSAR process.

Conclusion: The Future of DSAR Manageme

As data privacy regulations continue to evolve and the volume of personal data increases, the demand for efficient DSAR processing will only grow. Organisations that invest in technological tools to automate and streamline the DSAR process will be better positioned to meet these demands while ensuring compliance with data protection laws.

By leveraging DSAR automation platforms, AI-powered data discovery tools, self-service portals, automated redaction tools, data retention and deletion solutions, and collaboration tools, organisations can significantly reduce the complexity and cost associated with responding to DSARs. These technologies not only simplify the process but also mitigate the risk of errors, ensuring that individuals’ rights are respected and that organisations remain compliant with privacy regulations.

The future of DSAR management lies in continued innovation and the adoption of AI and machine learning technologies, which will further enhance the accuracy and efficiency of the process. For organisations, staying ahead of the curve by implementing these tools is essential for maintaining compliance and building trust with their customers in an increasingly privacy-conscious world.