10 Steps to Complete the DSAR Process

Author

Anas Baig

Product Marketing Manager at Securiti

Published November 24, 2023

Listen to the content

Data Subject Rights (DSRs) are a fundamental component of data privacy and protection regulations like the European Union’s General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA) now amended by the California Privacy Rights Act (CPRA), and various other data privacy regulations worldwide.

DSRs empower individuals to exercise control over their personal data. Various DSRs under global data privacy laws and regulations include the right to be informed, right to access, right of rectification, right to erasure/right to be forgotten, right to restrict processing, right to data portability, right to object to data processing activities, and the rights related to automated decision making, including profiling.

Handling DSR requests effectively is crucial for organizations to ensure compliance and maintain trust with data subjects. This guide will explore ten essential steps to completing a data subject request to exercise the right to access (DSAR).

DSAR Response Time Frames

Before we dive into the DSAR process, it's crucial to establish the correct timeframe for a DSAR response process. There are different deadlines for DSAR compliance. For instance, under the CCPA, organizations must respond to a DSAR within 45 days of receiving it.

On the other hand, DSARs under the EU and UK GDPR must be responded to within 30 days following their receipt. Under Article 12 of the GDPR, data controllers must respond to a DSAR “without undue delay” and “in any event within one month of receipt of the request”.

Under Canada’s Personal Information Protection and Electronic Documents Act (PIPEDA), organizations are obliged to respond to the request for personal information within 30 calendar days of receipt of a request for it. Organizations cannot simply acknowledge within 30 days that they received the request and then take more time actually to deal with it.

Step 1 – Identify and Document DSARs

Identifying and documenting the request is the first step in the DSAR process. This may be received by phone, email, or even an online form. A robust DSAR process must be in place to swiftly document and log these requests. Accurate identification and documentation at this step lay the foundation for effective DSAR management throughout the entire process.

To ensure compliance with evolving data protection laws and to provide a transparent and easy-to-use process for data subjects and the organization, it is imperative to establish a systematic approach for documenting and handling existing and upcoming DSARs.

Step 2 – Verify the Requestor's Identity

This crucial stage verifies that the requester of the data access is, in fact, the individual they claim they are. Confirm the individual's identity to prevent unauthorized access to sensitive data. Verification usually entails validating their identity using secure tools, such as official identification documents, login credentials, or other authorized methods.

Step 3 – Locate and Access Data Sources

After verifying the requestor's identity, the organization must begin the complex and multifaceted task of locating and accessing the requested personal data, which may be spread across several departments, databases, formats, native systems, and cloud and multi-cloud environments.

It is imperative to establish an effective and systematic data retrieval process to comply with the evolving requirements of data privacy laws and ensure prompt and correct responses to DSARs. During this step, it's critical to demonstrate transparency by informing the data subject of their request's status.

Step 4 – Retrieve the Requested Data

The next step is to extract and compile the specific personal data that the data subject has requested. This may entail obtaining data from various sources, including files, databases, emails, etc.

This step requires special consideration as it is critical to ensure that the data provided is accurate, in line with the request made by the data subject, and without any unnecessary data. Additionally, data protection regulations require that the process be carried out securely, maintaining the privacy of the data at all times and within the permitted time frame.

Step 5 – Review Data for Exemptions

Thoroughly examine the retrieved data for any exemptions or redaction requirements, as data privacy regulations may legally protect some personal data and may contain third-party data that should not be disclosed or shared with the data subject.

Step 6 – Organize and Format the Data

Provide the data subject with their data in a clear, structured, understandable format and user-friendly manner. This may involve preparing a detailed report of the data subject’s data or providing them access to a secure portal where they can review their data.

Data may need to be organized systematically and converted into a widely utilized format, such as Excel or PDF. This enables the data subject to examine and use the data efficiently, enhancing transparency and facilitating a seamless experience in exercising their DSARs.

Step 7 – Secure Data Transmission

Once the required personal data has been organized and formatted, it is ready for delivery to the data subject. To safeguard data from any breaches or leaks, organizations must ensure that such transfers are carried out using the highest security standards. This includes transferring the data over secure networks or via secure file-sharing methods.

Step 8 – Document the Process

Maintain thorough documentation of the DSAR process, including every step carried out, the response given, and any exemptions used. This includes details about the request, verification techniques, data retrieval process, applicable exemptions, data format used, and data transfers made via a secure channel.

Aside from providing proof of compliance with applicable data protection laws, maintaining documentation enables organizations to monitor the entire DSAR process, identify improvement areas, and demonstrate accountability in case of audits or investigations.

Step 9 – Communicate with the Requestor

Throughout the DSAR process, constantly communicate with the requestor regarding each step, how things are going, if there are any delays, and when they may expect to receive the needed data. This correspondence should include specifics of the data that has been provided, addressing any ambiguities, and contact details in case of confusion.

Step 10 – Close the DSAR

Close the DSAR after the data subject has received the requested information. This includes getting the data subject to attest that their request has been fulfilled, resolving any issues that may still exist, and making sure they are informed that the procedure is finished.

Closing the DSAR demonstrates the conclusion of the data subject's request for their data and assists organizations in keeping an accurate record of their compliance with applicable data protection laws. This last step guarantees that the organization has honored the data subject's rights and that their request has been properly handled.

How Securiti Can Help

As data privacy regulations evolve, organizations that invest in robust DSAR automation tools will be better equipped to meet the growing expectations of a data-conscious society while maintaining compliance and confidence with their data subjects.

Securiti DSR automation is the most efficient and modern way to honor DSAR. Businesses can save money during the DSAR process, lower their risk of compliance fines dramatically, and maintain brand integrity by implementing automation.

Request a demo to witness Securiti in action.

Analyze this article with AI

Prompts open in third-party AI tools.
Join Our Newsletter

Get all the latest information, law updates and more delivered to your inbox



More Stories that May Interest You
Videos
View More
Rehan Jalil, Veeam on Agent Commander : theCUBE + NYSE Wired: Cyber Security Leaders
Following Veeam’s acquisition of Securiti, the launch of Agent Commander marks an important step toward helping enterprises adopt AI agents with greater confidence. In...
View More
Mitigating OWASP Top 10 for LLM Applications 2025
Generative AI (GenAI) has transformed how enterprises operate, scale, and grow. There’s an AI application for every purpose, from increasing employee productivity to streamlining...
View More
Top 6 DSPM Use Cases
With the advent of Generative AI (GenAI), data has become more dynamic. New data is generated faster than ever, transmitted to various systems, applications,...
View More
Colorado Privacy Act (CPA)
What is the Colorado Privacy Act? The CPA is a comprehensive privacy law signed on July 7, 2021. It established new standards for personal...
View More
Securiti for Copilot in SaaS
Accelerate Copilot Adoption Securely & Confidently Organizations are eager to adopt Microsoft 365 Copilot for increased productivity and efficiency. However, security concerns like data...
View More
Top 10 Considerations for Safely Using Unstructured Data with GenAI
A staggering 90% of an organization's data is unstructured. This data is rapidly being used to fuel GenAI applications like chatbots and AI search....
View More
Gencore AI: Building Safe, Enterprise-grade AI Systems in Minutes
As enterprises adopt generative AI, data and AI teams face numerous hurdles: securely connecting unstructured and structured data sources, maintaining proper controls and governance,...
View More
Navigating CPRA: Key Insights for Businesses
What is CPRA? The California Privacy Rights Act (CPRA) is California's state legislation aimed at protecting residents' digital privacy. It became effective on January...
View More
Navigating the Shift: Transitioning to PCI DSS v4.0
What is PCI DSS? PCI DSS (Payment Card Industry Data Security Standard) is a set of security standards to ensure safe processing, storage, and...
View More
Securing Data+AI : Playbook for Trust, Risk, and Security Management (TRiSM)
AI's growing security risks have 48% of global CISOs alarmed. Join this keynote to learn about a practical playbook for enabling AI Trust, Risk,...

Spotlight Talks

Spotlight 59:11
Data Controls for AI: Findings from the 2026 GigaOm DSPM Research
Watch Now View
Spotlight 1:02:06
Consent by proxy: When AI agents start deciding for us
Watch Now View
Spotlight 1:00:41
Future-Proofing for the Privacy Professional
Watch Now View
Spotlight 50:52
From Data to Deployment: Safeguarding Enterprise AI with Security and Governance
Watch Now View
Spotlight 11:29
Not Hype — Dye & Durham’s Analytics Head Shows What AI at Work Really Looks Like
Not Hype — Dye & Durham’s Analytics Head Shows What AI at Work Really Looks Like
Watch Now View
Spotlight 11:18
Rewiring Real Estate Finance — How Walker & Dunlop Is Giving Its $135B Portfolio a Data-First Refresh
Watch Now View
Spotlight
Choosing the Right DSPM: An Industry Analyst’s Perspective
Watch Now View
Spotlight 13:38
Accelerating Miracles — How Sanofi is Embedding AI to Significantly Reduce Drug Development Timelines
Sanofi Thumbnail
Watch Now View
Spotlight 10:35
There’s Been a Material Shift in the Data Center of Gravity
Watch Now View
Spotlight 14:21
AI Governance Is Much More than Technology Risk Mitigation
AI Governance Is Much More than Technology Risk Mitigation
Watch Now View
Latest
Australia’s Office of AI: Why Annual Audits Miss What Your AI Can Reach View More
Australia’s Office of AI: Why Annual Audits Miss What Your AI Can Reach
Picture this: a fictional but entirely plausible scenario. An Australian financial institution's AI systems spend six months accessing a customer data repository nobody has...
View More
A Complete DSPM Needs Classification and Context
Classification is one of the core functions a DSPM program handles, and it usually runs in tandem with discovery, since together they form the...
View More
DSPM for AI: Extending Data Posture to Prompts, Pipelines & Agents
Learn how DSPM for AI helps enterprises discover sensitive data, assess exposure, govern access, reduce risk, and secure data before AI systems and agents...
DSPM vs DLP: Key Data Security Differences Explained View More
DSPM vs DLP: Key Data Security Differences Explained
Compare DSPM vs DLP to understand how they differ in data discovery, classification, monitoring, prevention, risk reduction, and protecting sensitive enterprise data.
The Context Layer for Data+AI Security View More
The Context Layer for Data+AI Security
Discover how Securiti’s DataAI Command Graph connects data, identity, cloud, and AI findings to uncover contextual risk and toxic combinations.
View More
Privacy RFP Buyer’s Guide: 120+ Questions to Evaluate Privacy Automation Platforms
Download the Privacy RFP Buyer’s Guide with 120+ practical questions to evaluate privacy automation platforms across compliance, security, integrations, governance, and scalability.
The Toxic Combination Problem in DataAI Risks View More
The Toxic Combination Problem in DataAI Risks
Discover how siloed security alerts create hidden toxic risk combinations and how correlated context helps reduce alert fatigue and uncover compound risks faster.
The Cloud Storage Bill Nobody Reads View More
The Cloud Storage Bill Nobody Reads
Hidden cloud storage costs add up fast. Learn how redundant, obsolete, and trivial data drives unnecessary spend, expands risk, and why automated data minimization...
View More
Take the Data Risk Out of AI
Learn how to prepare enterprise data for safe Gemini Enterprise adoption with upstream governance, sensitive data discovery, and pre-index policy controls.
View More
Navigating HITRUST: A Guide to Certification
Securiti's eBook is a practical guide to HITRUST certification, covering everything from choosing i1 vs r2 and scope systems to managing CAPs & planning...
What's
New