Ensuring that you have clear objectives and a strong project plan will accelerate DSPM deployment and optimize project success. What follows are the typical steps that Enterprise Strategy Group has observed in successful DSPM implementations. Every organization is different, and the order and exact elements of the below steps will vary depending on your organization.

1. Stakeholder Alignment

Engage key stakeholders. Start by aligning key stakeholders, including governance, risk, and compliance (GRC) personnel, data teams, cloud architects, and security teams. Ensure that everyone understands the objectives, benefits, and their roles in the DSPM deployment process.

Define goals, definitions, and metrics. Collaboratively establish the goals of the DSPM initiative, such as reducing data exposure, achieving compliance, and improving overall data security posture. Arrive at what data is sensitive to the business and data classification definitions. Agree on key performance indicators to measure success.

Secure executive buy-in. Present a clear case to executives, highlighting the importance of DSPM in mitigating data risks, achieving regulatory compliance, and supporting business goals. Ensure top-down support for resource allocation and prioritization.

Assign roles and responsibilities. Clearly define the responsibilities of each team. GRC will focus on compliance and policy alignment, data teams will manage data classification and ownership, and security teams will oversee the implementation of security controls and monitoring.

2. Assess Current Data Environment

Inventory data stores. Begin by cataloging all data stores across your environment, including cloud, on-premises, SaaS, IaaS, PaaS, and hybrid systems. DSPM tools can help in this effort, particularly in identifying any unmonitored “shadow data” to which IT and security teams lack visibility.

3. Identify Exposed Data Stores and Begin Mitigating Risks

Discover exposed data. Use DSPM tools to scan and identify data stores that are exposed to potential threats, such as those lacking encryption or with open-access permissions.

Scan for misconfigurations. Regularly scan your environment for misconfigurations in data stores, access controls, and security settings.

Mitigate exposure and automate remediation. Implement immediate corrective actions, such as applying encryption, restricting public access, and ensuring proper authentication mechanisms. Use DSPM tools to automatically correct misconfigurations or flag them for immediate attention by the relevant teams.

4. Identify Data Stores With Critical Data

Valuable and sensitive data discovery. Locate data stores containing critical and sensitive data, including cardholder data (PCI DSS), protected health information, personally identifiable information, and data covered by GDPR.

Monitor access patterns. Regularly monitor these stores for unusual access patterns that could indicate potential security breaches.

5. Classify Data

Data classification. Categorize data based on sensitivity and compliance requirements of your organization. For example, use classifications like public, internal, sensitive, and restricted.

Automate classification. Consider implementing automated tools that can classify data in real time as it enters your environment, reducing manual effort.

6. Determine Necessary Security Controls Based on Classification

Apply security controls. Implement security measures such as encryption, tokenization, or masking based on the data’s classification level.

Continuous monitoring. Set up continuous monitoring for all data stores to detect unauthorized access or changes in data classification.

7. Identify and Delegate Data Owners

Assign ownership. Designate data owners who are responsible for managing access and ensuring compliance with security policies for each data store.

Document responsibilities. Clearly define the roles and responsibilities of data owners to avoid confusion and ensure accountability.

8. Identify Users with Access to Sensitive/Restricted Data

Access review. Regularly audit who has access to sensitive and restricted data to ensure it aligns with their role and responsibilities.

Justify access. Determine if access is necessary for their job function. If not, remove or restrict access.

9. Restrict Access to Need-to-know and Least Privilege

Enforce least privilege. Ensure that users only have access to the data they need for their job, following the principle of least privilege.

Implement role-based access control. Use RBAC to manage user permissions and restrict access based on job roles.

10. Segment Data Types to Control Sprawl of Restricted Data

Data segmentation. Segment data into different categories based on sensitivity, regulatory requirements, and business value that might require special treatment or controls.

Isolate critical data. Place sensitive and high-value data in isolated environments or segments with stricter security controls.

11. Determine Necessary Security Controls Based on Classification

Apply security controls. Implement security measures such as encryption, tokenization, or masking based on the data’s classification level.

Continuous monitoring. Set up continuous monitoring for all data stores to detect unauthorized access or changes in data classification.

12. Implement Continuous Compliance Checks

Automate compliance audits. Schedule regular audits to ensure ongoing compliance with industry regulations (e.g., PCI DSS, GDPR, HIPAA) and internal policies.

Generate compliance reports. Use DSPM tools to generate real-time compliance reports that can be shared with stakeholders and auditors.

13. Enable Observability by Establishing Alerts and Incident Response

Set up alerts. Configure your DSPM solution to trigger real-time alerts for any suspicious activity, such as unauthorized access attempts or data exfiltration.

Incident response plan. Develop and implement an incident response plan that specifies actions to take in the event of a security breach.

14. Evaluate and Iterate

Regular assessments. Periodically assess the effectiveness of your DSPM implementation and adjust as needed to address new threats or business changes.

Feedback loop. Establish a feedback loop with key stakeholders to continuously improve DSPM strategies and tools.

15. Do an Ongoing Validation of Classification and Remediation Steps

Continuous classification review. Regularly review and validate the accuracy of data classification to ensure that all sensitive data is properly identified, especially as data evolves or new types of data are introduced.

Remediation validation. Continuously validate that remediation steps taken to secure or remove sensitive data are effective. This includes verifying that access controls are enforced, encryption is properly applied, and data is securely deleted or archived as needed.

Audit and feedback loop. Implement an ongoing audit process to assess the effectiveness of your classification and remediation strategies. Collect feedback from stakeholders to identify any gaps or areas for improvement.

Automated validation. Utilize your DSPM solution to regularly validate that classification and remediation protocols are being followed correctly, ensuring compliance and security standards are consistently met.

16. Educate and Train Teams

Ongoing training. Provide regular training sessions for IT, security, and data teams to stay updated on DSPM practices, tools, and the latest threats.

Cross-team collaboration. Encourage collaboration between data owners, security teams, and compliance officers to ensure consistent data protection practices.