Cybercrimes are increasing at an accelerated rate. To put things into perspective, by 2025, the cost of cybercrime is predicted to hit a whopping $10.5 trillion annually. Statistics like these demand a significant need to enhance the data security posture in organizations across the globe. However, several obstacles affect the adoption of a robust data security framework, such as multi-cloud complexities, data and AI laws, and the limited capabilities of existing data detection and response, data loss prevention, and similar tools. Data Security Posture Management (DSPM) is a critical discipline that turns an organization’s focus from an infrastructure-first to a data-first approach to cyber security. This blog will discuss DSPM and the key capabilities and factors to consider when buying a solution for your data security needs. What is Data Security Posture Management (DSPM)? DSPM stands for Data Security Posture Management. Gartner coined the term DSPM a few years back in its Hype Cycle report. Gartner highlighted the need for enhanced data security measures or approaches to help prevent the growing instances of data breaches and overcome the complexities of multi-cloud that lead to those breaches. As mentioned earlier, DSPM is a data-centric approach to data security, be it for on-premises data stores, SaaS services, or hybrid multi-cloud environments. The solutions provide detailed insights into the existence and location of sensitive data across the environment, who accesses it or how it is accessed, and the security posture of the application or data stores where it resides. Core Capabilities of DSPM Organizations seeking the right DSPM solution to reinforce their data security strategy must recognize that not all solutions are created equal. In 2024, GigaOm released its first-ever assessment of DSPM in its Radar report. The research firm highlighted some key capabilities that must be fundamentally available in a robust DSPM solution. Let’s take a look at those capabilities. Data Discovery Data security starts with gaining visibility of all data assets across an organization, including its on-premise data stores, SaaS services, and other cloud environments, leaving no stone unturned. The DSPM solution helps an organization do that by automatically discovering its structured and unstructured data assets. Data Classification DSPM solutions automatically scan environments to identify and classify sensitive data based on its business value, regulatory requirements, and other industry-specific policies upon discovering data assets. Data classification is a critical process that helps organizations set appropriate controls and prioritize their most sensitive data. Data Flow Data movement across an organization's various systems, data stores, and applications is dynamic. Teams must visualize and understand the data flow across systems to evaluate its privacy and security controls. DSPM helps visually illustrate the data movement, enabling teams to trace the transformation of data and the associated risks. Risk Assessment Another critical feature of a DSPM solution is that it gives teams insights into the risks through a thorough assessment. DSPM continuously monitors the environments for various vulnerabilities, assigns risk ratings, and helps teams prioritize remediation. Data Access Governance One critical threat to sensitive data is excessive privileges that lead to unauthorized access or inadvertent exposure. DSPM leverages access insights and IAM integrations to help organizations gain visibility of data access and risks and set up appropriate access policies and controls based on users, roles, and permissions. It further paves the way to the principle of least privilege (PoLP). Security Controls Apart from access governance, DSPM further enables organizations to place appropriate security controls based on the classification of data and its relevant risk scores. Such controls may include data encryption at rest or in motion, dynamic data masking for secure sharing practices, etc. DSPM also helps automate the security controls across the environments to minimize the risk of human error. Data Lineage From data ingestion to retention, data transformation occurs continuously and rapidly. Tracking such transformation across its lifecycle becomes difficult when handling data at the petabyte scale. DSPM allows organizations to overcome this challenge by tracking the changes over time. Breach Response DSPM solutions are well-equipped to respond to data breaches as soon as they are detected. The tool leverages breach impact insights, such as the volume of data impacted, the affected identities, and the relevant regulatory requirements. These insights help the tool to automatically isolate the impacted systems, revoke access permissions on compromised data, and initiate the notification process. Enterprise Stack Integration DSPM shouldn't be just another siloed integration among other tools. In fact, it should offer a unified approach to data security by seamlessly integrating with the existing security stack. This key operational factor ensures that workflows remain seamless and the organization can maximize the security stack's value. Secure AI Like many other technologies, DSPM tools had to respond to AI's growing adoption and its unprecedented risks. The OWASP Top 10 for LLM Applications feature the top-most critical risks that could compromise the AI systems development lifecycle, resulting in legal fines, compliance violations, and reputational loss. Hence, advanced DSPM solutions must offer much-needed capabilities like data sanitization and redaction or LLM firewalls to help organizations safely adopt AI. Important Factors to Consider While keeping in mind the aforementioned capabilities, organizations should also consider the following factors when looking for a robust DSPM solution. Agentless Discovery It is imperative to ensure that the solution offers agentless data discovery across the organization's environment. This capability is necessary to enable fast data discovery and mapping while minimizing deployment complexities. Centralized Dashboard The tool should provide a centralized dashboard that aggregates various metrics and reports, allowing teams to simplify monitoring and provide real-time insights to stakeholders. Continuous Detection and Prioritization of Critical Data Exposure The solution should identify the most critical threats to the organization's security posture and implement immediate remediation controls. Data Lineage Mapping The tool should further offer data lineage capabilities, providing organizations with visibility into the transformation of their sensitive data over time. By tracking the data's lineage across its lifecycle, security teams can better understand the security gaps and thus establish optimized controls and policies. Automated Remediation DSPM tools should allow security teams to respond automatically to security incidents when they occur. This capability is essential in ensuring the integrity and confidentiality of the data. Scalability and Performance Lastly, organizations with hyper-scale environments should look for a DSPM tool that scales to accommodate the needs of their rapidly growing data. Cybercrimes are increasing at an accelerated rate. To put things into perspective, by 2025, the cost of cybercrime is predicted to hit a whopping $10.5 trillion annually. Statistics like these demand a significant need to enhance the data security posture in organizations across the globe. Cybercrimes are increasing at an accelerated rate. To put things into perspective, by 2025 , the cost of cybercrime is predicted to hit a whopping $10.5 trillion annually. Statistics like these demand a significant need to enhance the data security posture in organizations across the globe. 2025 2025 However, several obstacles affect the adoption of a robust data security framework, such as multi-cloud complexities, data and AI laws, and the limited capabilities of existing data detection and response, data loss prevention, and similar tools. However, several obstacles affect the adoption of a robust data security framework, such as multi-cloud complexities, data and AI laws, and the limited capabilities of existing data detection and response, data loss prevention, and similar tools. Data Security Posture Management ( DSPM ) is a critical discipline that turns an organization’s focus from an infrastructure-first to a data-first approach to cyber security. DSPM DSPM This blog will discuss DSPM and the key capabilities and factors to consider when buying a solution for your data security needs. What is Data Security Posture Management (DSPM)? DSPM stands for Data Security Posture Management . Gartner coined the term DSPM a few years back in its Hype Cycle report. Gartner highlighted the need for enhanced data security measures or approaches to help prevent the growing instances of data breaches and overcome the complexities of multi-cloud that lead to those breaches. Data Security Posture Management As mentioned earlier, DSPM is a data-centric approach to data security, be it for on-premises data stores , SaaS services, or hybrid multi-cloud environments. The solutions provide detailed insights into the existence and location of sensitive data across the environment, who accesses it or how it is accessed, and the security posture of the application or data stores where it resides. data stores data stores Core Capabilities of DSPM Organizations seeking the right DSPM solution to reinforce their data security strategy must recognize that not all solutions are created equal. In 2024, GigaOm released its first-ever assessment of DSPM in its Radar report . The research firm highlighted some key capabilities that must be fundamentally available in a robust DSPM solution. Let’s take a look at those capabilities. GigaOm released its first-ever assessment of DSPM in its Radar report Data Discovery Data security starts with gaining visibility of all data assets across an organization, including its on-premise data stores, SaaS services, and other cloud environments, leaving no stone unturned. The DSPM solution helps an organization do that by automatically discovering its structured and unstructured data assets. Data Classification DSPM solutions automatically scan environments to identify and classify sensitive data based on its business value, regulatory requirements, and other industry-specific policies upon discovering data assets. Data classification is a critical process that helps organizations set appropriate controls and prioritize their most sensitive data. Data Flow Data movement across an organization's various systems, data stores, and applications is dynamic. Teams must visualize and understand the data flow across systems to evaluate its privacy and security controls. DSPM helps visually illustrate the data movement, enabling teams to trace the transformation of data and the associated risks. Risk Assessment Another critical feature of a DSPM solution is that it gives teams insights into the risks through a thorough assessment. DSPM continuously monitors the environments for various vulnerabilities, assigns risk ratings, and helps teams prioritize remediation. Data Access Governance One critical threat to sensitive data is excessive privileges that lead to unauthorized access or inadvertent exposure. DSPM leverages access insights and IAM integrations to help organizations gain visibility of data access and risks and set up appropriate access policies and controls based on users, roles, and permissions. It further paves the way to the principle of least privilege (PoLP). Security Controls Apart from access governance, DSPM further enables organizations to place appropriate security controls based on the classification of data and its relevant risk scores. Such controls may include data encryption at rest or in motion, dynamic data masking for secure sharing practices, etc. DSPM also helps automate the security controls across the environments to minimize the risk of human error. Data Lineage From data ingestion to retention, data transformation occurs continuously and rapidly. Tracking such transformation across its lifecycle becomes difficult when handling data at the petabyte scale. DSPM allows organizations to overcome this challenge by tracking the changes over time. Breach Response DSPM solutions are well-equipped to respond to data breaches as soon as they are detected. The tool leverages breach impact insights, such as the volume of data impacted, the affected identities, and the relevant regulatory requirements. These insights help the tool to automatically isolate the impacted systems, revoke access permissions on compromised data, and initiate the notification process. Enterprise Stack Integration DSPM shouldn't be just another siloed integration among other tools. In fact, it should offer a unified approach to data security by seamlessly integrating with the existing security stack. This key operational factor ensures that workflows remain seamless and the organization can maximize the security stack's value. Secure AI Like many other technologies, DSPM tools had to respond to AI's growing adoption and its unprecedented risks. The OWASP Top 10 for LLM Applications feature the top-most critical risks that could compromise the AI systems development lifecycle, resulting in legal fines, compliance violations, and reputational loss. Hence, advanced DSPM solutions must offer much-needed capabilities like data sanitization and redaction or LLM firewalls to help organizations safely adopt AI. Important Factors to Consider While keeping in mind the aforementioned capabilities, organizations should also consider the following factors when looking for a robust DSPM solution. Agentless Discovery It is imperative to ensure that the solution offers agentless data discovery across the organization's environment. This capability is necessary to enable fast data discovery and mapping while minimizing deployment complexities. Centralized Dashboard The tool should provide a centralized dashboard that aggregates various metrics and reports, allowing teams to simplify monitoring and provide real-time insights to stakeholders. Continuous Detection and Prioritization of Critical Data Exposure The solution should identify the most critical threats to the organization's security posture and implement immediate remediation controls. Data Lineage Mapping The tool should further offer data lineage capabilities, providing organizations with visibility into the transformation of their sensitive data over time. By tracking the data's lineage across its lifecycle, security teams can better understand the security gaps and thus establish optimized controls and policies. Automated Remediation DSPM tools should allow security teams to respond automatically to security incidents when they occur. This capability is essential in ensuring the integrity and confidentiality of the data. Scalability and Performance Lastly, organizations with hyper-scale environments should look for a DSPM tool that scales to accommodate the needs of their rapidly growing data.

DSPM Buyer’s Guide: Key Factors to Consider

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

From CCPA to CPRA: 5 Actionable Steps Every Business Should Follow

A Guide To Protecting Sensitive Business Data

An Introduction to 4 Types of Audio Classification

Mastering Logistic Regression: A Comprehensive Guide with Practical Example

Using AWS Macie To Classify Databases

Designing For Security: What You Need to Know

From CCPA to CPRA: 5 Actionable Steps Every Business Should Follow

A Guide To Protecting Sensitive Business Data

An Introduction to 4 Types of Audio Classification

Mastering Logistic Regression: A Comprehensive Guide with Practical Example

Using AWS Macie To Classify Databases

Designing For Security: What You Need to Know

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps