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Enhancing Data Governance with Data Security Posture Management (DSPM)

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In today’s data-driven world, organizations are constantly grappling with the challenge of managing vast volumes of data while ensuring its security, integrity, and compliance with regulations. Data governance, as a comprehensive framework, has emerged as a solution to tackle these challenges effectively. Data governance refers to the overall management and control of an organization’s data assets. Data governance best practices encompass the processes, policies, and procedures that govern how data is collected, stored, organized, accessed, and used within an organization. The primary goal of data governance is to ensure the quality, integrity, security, and compliance of data throughout its lifecycle.

Effective data governance helps organizations maximize the value of their data assets, make informed decisions based on reliable and accurate data, mitigate risks associated with data breaches or non-compliance, and build trust with stakeholders. It also promotes collaboration and consistency in data management practices across the organization. 

Data security posture management

One way to augment and complement effective data governance is to follow data security posture management (DSPM) principles. DSPM focuses on assessing, managing, and enhancing an organization’s security posture to protect its data assets effectively. It specifically addresses these four core questions – where is my sensitive data, who has access to that data, how has this data been used and what is my security posture1

According to Gartner1, DSPM serves as the foundation for a data risk assessment that assesses the effectiveness of data security governance policies. Below are 6 ways an organization can leverage DSPM principles to enhance data governance.

Comprehensive Data Inventory

DSPM principles emphasize having a thorough understanding of an organization’s data assets. By conducting a comprehensive data inventory, organizations can identify and classify sensitive data, map data flows, and determine the data’s criticality and associated risks. This inventory serves as a foundation for effective data governance practices.

Risk Assessment and Prioritization

DSPM involves assessing the risks associated with data assets. Organizations can prioritize their data governance efforts by evaluating the vulnerabilities, threats, and potential impacts on data confidentiality, integrity, and availability. This helps in identifying the most critical areas that require immediate attention and resource allocation.

Security Controls and Compliance

DSPM principles encourage the implementation of robust security controls to protect data. Organizations can establish data protection measures such as encryption, access controls, data loss prevention (DLP) solutions, and intrusion detection systems. These controls aid in compliance with data protection regulations and industry standards, reinforcing data governance practices.

Continuous Monitoring and Remediation

DSPM emphasizes continuous monitoring of an organization’s security posture. By implementing security monitoring solutions and conducting regular assessments, organizations can detect and respond to security incidents promptly. This proactive approach helps in identifying vulnerabilities or non-compliance with data governance policies, enabling timely remediation actions.

Incident Response and Data Breach Mitigation

DSPM principles contribute to effective incident response and data breach mitigation. Organizations can establish incident response plans that outline the steps to be taken in the event of a security incident or data breach. By implementing incident response frameworks, organizations can minimize the impact of breaches, protect affected data, and fulfill their incident response obligations, which are essential for data governance.

Integration and Automation

DSPM principles advocate for integration and automation of security controls and monitoring systems. By integrating various security solutions, organizations can streamline data governance processes, improve efficiency, and ensure consistent application of security measures. Automation can assist in data discovery, classification, and monitoring, enhancing the overall effectiveness of data governance efforts.

Effective data governance requires a holistic understanding of an organization’s data, including its sensitivity, access, usage, and security posture. DSPM provides a comprehensive approach that empowers organizations to enhance their data governance strategy. By leveraging DSPM capabilities, organizations can gain visibility into sensitive data, control access, track data usage, ensure compliance, and continuously assess and improve their data security posture. By embracing DSPM, organizations can achieve robust data governance that safeguards data assets, mitigates risks, and maintains regulatory compliance in an increasingly data-centric landscape.

As DSPM becomes a vital need for all midsize and enterprise organizations, Qohash emerges as the preferred choice with our distinct ability to track individual data elements at scale. To learn more about Qohash’s DSPM platform, contact our sales team!

1 Gartner, Hype Cycle for Data Security, 2022, Brian Lowans, 04 August 2022.

The Gartner document is available upon request from Qohash.

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