Key Aspects of Data Access Governance in Compliance and Auditing

What is Data Access Governance?

80% of digital organizations will fail because they don’t take a modern approach to data governance. (Gartner)

Data is widely recognized as the most valuable business asset. Tapping into your company’s data is appealing, but caution must be taken to ensure that sensitive information does not get into the wrong hands.

Data access governance is a subset of data governance. It refers to the methods and technology businesses employ to manage and monitor access to their data. Access governance guarantees that authorized individuals or processes have access to the right data at the right time while protecting sensitive information from unauthorized disclosure.

“Data access governance” is often associated with strict rules and regulations to keep sensitive data under lock and key. This is because the traditional approach to data access governance uber-focuses on data access governance controls for fear of data falling into the wrong hands. 

Modern access governance shifts the emphasis from data limitation to data enablement. Data enablement is about ensuring that the correct individuals have access to the data they require at the right time while reducing bottlenecks caused by dependencies.

Adopting a “trust but verify” based on a Zero Trust model significantly allows teams to easily and securely provide data access for internal team members and trusted third parties.

Data Governance Goals

• Make data-driven business decisions
• Help data flow freely throughout the company 
• Instill trust and build confidence in data management 
• Facilitate compliance

Data Access Governance Goals

• Ensuring that only authorized users and systems can view, modify, or share sensitive data by mapping access to the data
• Monitoring and identifying anomalous access patterns or data transfers, which could signal a red flag
• Implementing standardized policies and procedures for managing data access across hybrid environments
• Maintaining a comprehensive view of data access across the enterprise

Fundamental Concepts in Data Access Governance

1. Least Privilege Access: Least privilege access reduces blast radius in the case of a breach by blocking unnecessary data access. Restricting privileges significantly lessens the likelihood of unwanted data exposure.

2. Segregation of Duties: Segregation of duties is the idea that no user has complete authority over critical systems, processes, or activities. For example, one team member can only perform a task with the assistance of another person. Segregation of duties is meant to prevent security breaches and guarantees that no single user has full control over vital information.

3. Continuous Monitoring: Regular monitoring of user activity and access permissions is essential to discover any patterns of suspicious behavior or policy violations. User and entity behavior analytics (UEBA) is an advanced feature that builds a behavioral baseline for users and devices to identify deviations that indicate abnormal or suspicious activities. 

4. Logging and Audit Trail: Establishing systems to track and register user behaviors and creating an audit trail for accountability are essential steps in establishing accountability.

Data Access Governance in Compliance and Auditing

One of the primary reasons businesses choose to implement a data access governance solution is compliance. Data governance guarantees that the data ecosystem follows the laws and regulations governing data access.

Businesses must comply with various data protection and privacy standards, including GDPR, HIPAA, CCPA, and PCI DSS. These frameworks impose stringent restrictions and audit requirements on how data is accessed.

Key features of data access governance in compliance and auditing are:

• Understanding that sensitive data needs greater access control
• Implementing access rules that are compliant with regulatory standards
• Monitoring data access for infractions
• Configuring cloud data access governance
• Mapping and generating reports on data governance access controls

Software Used for Data Access Governance

• DSPM

DSPM focuses on identifying, classifying, and securing data. It provides visibility into critical data assets, roles, and permissions across numerous cloud environments. DSPM also helps prioritize and manage access hazards and streamline governance-related duties. 

• Identification and Access Management (IAM)

IAM technology enables enterprises to manage user identities, access controls, and permissions across numerous systems and applications. It is used to revoke or grant permissions but needs a contextual understanding of the data stored in each cloud resource.

• Data Loss Prevention (DLP)

Data loss prevention (DLP) solutions aim to prevent data leakage, whether deliberate or unintentional. They monitor, detect, and prevent sensitive data transmission, and they frequently include data access governance tools to help manage access to sensitive data.

Underlying Principles of Data Access Governance

Strong data access governance is often centered around the following four important principles:

Integrity 

Data integrity ensures that data is accurate, complete, and valid. 

The relevance of data integrity grows as data volumes expand. Major enterprises increasingly use their data to understand consumer behavior and influence marketing activity.

Transparency

Transparency—both within and outside the organization—is critical to preserving accuracy while gathering and using data and authorizing access. Employees who do not understand what categories of data they have or use will struggle to protect that data adequately. 

Organizations should first ensure that the business collects and handles data correctly and then ensure that its data policies clearly communicate the purpose and proper use of the organization’s data. They should also ensure that the company is honest in describing its data collection and access procedures to customers and regulators if needed. 

Accountability 

Policies are pointless if they are consistently ignored. That is true whether everyone violates a policy or just one person does. Organizations must enforce their data access governance policies across the board, holding employees accountable for knowing and adhering to those policies regardless of their position. 

Consistency 

An organization’s data and access management strategies must be consistent to be effective. Consistency also requires departments to work together to be on the same page.

Benefits of Data Access and Governance

Strong data access governance benefits firms in various industries, including financial services, retail, and healthcare. The following list contains four advantages that data access governance can provide enterprises.

1. Protection from Cyberattacks

An organization that allows broad access to its data is more likely to encounter malware (such as a virus or ransomware) since cyber attackers can infiltrate the network through a larger field of users. Limiting data access to only those who require it lowers the danger of a cyberattack and simplifies risk mitigation by reducing the attack surface.

2. Prevention of Data Leaks

Current or former workers and individuals with access to organizational data may purposefully or unintentionally disclose trade secrets and other confidential information. However, they cannot disclose sensitive material they cannot access. Strong data access governance enables organizations to protect sensitive data from unauthorized disclosure and decrease the number of potential leaks.

3. Increased Compliance

The rapid growth of organizational data has coincided with a significant increase in data regulation. Financial, healthcare and government organizations are now subject to more stringent data privacy requirements.

Data access governance is a critical component of every organization’s compliance program. It enables enterprises to protect sensitive data such as personnel records and protected health information (PHI) under the Health Insurance Portability and Accountability Act of 1996 (HIPAA). 

It also allows organizations to demonstrate their efforts to comply with applicable rules and regulations to government agencies. This helps firms avoid the most serious regulatory implications, such as lengthy investigations and large fines.

4. Reputational Risk

Data breaches and regulatory actions can significantly hurt an organization’s brand. By strengthening their approach to data access governance, firms may demonstrate to regulators, consumers, and the general public that they value data privacy and security.  

10 Data Access Governance Best Practices

Here are ten best practices to get you started.

1. Document Data Access Policies: Establish explicit policies that specify who has access to what data within your organization. Document the procedures for requesting, permitting, and canceling access to sensitive information.

2. Implementing Role-Based Access Control (RBAC): Use RBAC to control access rights based on job roles and responsibilities. This guarantees that employees can only access the information required for their job tasks.

3. Regular Access Audits: Conduct periodic reviews of user access rights to verify they align with current job duties and responsibilities. Remove access for personnel who no longer need it.

4. Employee Training and Awareness: Employees should receive extensive training on data security best practices, including how to handle sensitive data responsibly and securely. Ensure they understand the significance of data protection and their involvement in data security.

5. Strong Authentication Measures: Use multi-factor authentication (MFA) to ensure only authorized users can access sensitive data. Use long, secure passwords and update them frequently.

6. Encrypt Sensitive Data: Encrypt sensitive data in transit and at rest to prevent unwanted access. Use encryption methods to protect data on servers, databases, and IoT digital devices.

7. Limit Access to the Need-to-Know Basis: Apply the principle of least privilege by allowing data access only to those who need it. Limit access to sensitive data to only those employees who require it to do their jobs.

8. Monitor and log access: Set up systems to track who has access to sensitive data. Review access logs and audit trails regularly for signs of unauthorized access or questionable activities.

9. Data Backup and Recovery: Implement frequent data backup practices to protect crucial information in the case of data loss or corruption. Backup systems should be tested regularly to ensure they are functional and reliable.

10. Vendor and Third-Party Access Controls: If your company relies on third-party suppliers or partners for data processing or storage, ensure that suitable access controls are in place to protect your information. Implement contracts or agreements that specify data security obligations and responsibilities.

What Does Data Auditing Entail? 

A data audit thoroughly assesses how your organization handles personal data. The GDPR sets strict guidelines for how personal data should be managed and protected. A data audit involves examining all aspects of data processing within an organization. 

A GDPR data audit aims to ensure that organizations are processing personal data lawfully, fairly, and transparently and that they are taking appropriate measures to protect individuals’ privacy rights. It helps organizations identify and address any compliance gaps.

Data audits entail: 

• Data inventory
• Data flow mapping
• Data processing activities
• Data storage locations
• Data access controls
• Data security measures
• Data retention policies
• Data subject rights
• Data breach response
• Documentation and records
• Monitoring and logging

Through this audit, you can uncover potential compliance issues and ensure that your organization adheres to data protection laws. 

Privacy laws like the GDPR and the CPRA will likely become more stringent with time.

Achieving Your Long-Term Goals with Data Governance Audits 

A data audit aims to enhance and protect organizational value. By implementing effective data risk management, organizations guarantee that their data assets are obtained, kept, and used in a way that allows them to make data-driven business decisions.