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Cybercrime costs are projected to hit $10.5 trillion annually by 2025. This alarming statistic, and many others, reflects the critical need to reinforce your organization’s data security strategy. However, challenges like growing multi-cloud complexities, the ever-evolving data privacy laws, the limited capabilities of traditional DLP or CNAPP tools, and emerging GenAI threats pose significant obstacles.
Here, data security procurement management (DSPM) comes into play—as a data-centric approach to reinforcing data security.
This article will explore DSPM and how this technology can address your organization's specific data security objectives. We will cover DSPM’s core concepts, key capabilities, and critical features to consider when selecting a DSPM solution.
Data Security Posture Management (DSPM) provides organizations with visibility of sensitive data—local and in the cloud—enabling them to continuously assess risks associated with data access, exposure, and misconfiguration, implement appropriate security controls, and ensure compliance data protection standards.
In its 2022 Hype Cycle™ for Data Security report, Gartner highlighted the urgent need for robust data security measures due to heightened multi-cloud adoption and increasing data security breaches. In the report, Gartner coined the term DSPM as a new category aimed at transforming how organizations can protect their data and urged them to rethink a traditional, piecemeal approach to posture management.
Further defining this approach, GigaOm defined DSPM in its GigaOm Radar for Data Security Posture Management Report (DSPM) report as a solution that provides
“visibility into where sensitive data is, who has access to it, and how it is being used. DSPM gives a comprehensive view of an organization’s data security posture, its compliance position, security and privacy risks, and, crucially, how to deal with them.”
DSPM leads with a data-first stance for protecting cloud data. It shifts organizations' usual inclination to treat data as the last frontier and prioritizes the protection of networks, systems, and resources.
With this practical and proactive approach, DSPM aligns with the latest security frameworks (such as the Center for Internet Security’s (CIS) Critical Security Controls and the National Institute of Standards and Technology (NIST) framework), treating data security as a top priority. It addresses the regulatory needs of ubiquitous data protection laws like the European Union’s General Data Protection Regulation (GDPR) and the California Privacy Rights Act (CPRA) to implement strict security measures to protect personal and sensitive personal data.
Securiti’s Data Command Center dominates GigaOm’s DSPM Evaluation with highest ratings for key capabilities, emerging capabilities, and business criteria.
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Overall, DSPM paves a strategic path to proactively assess everything that potentially affects the overall security posture of an organization’s data landscape. More importantly, going back to GigaOm’s definition of DSPM, it enables organizations to answer the most concerning questions that make up the backbone of a robust data security ecosystem:
A DSPM framework must address these concerns to be effective and inclusive.
Hybrid and multi-cloud deployments are now the major focus of most organizations globally. To put that in perspective, CISCO cites in its 2022 Global Hybrid Cloud Trends Report that 82% of IT leaders flocked toward hybrid cloud adoption in 2022. Both hybrid and multi-cloud environments are known for their speed, efficiency, and scalability.
However, the innate complexities of these environments render many organizations unable to ensure a consistent security posture of their data landscape. DSPM helps effectively manage and protect data in such environments by providing comprehensive visibility of sensitive data and controls over sensitive data access, governance policies, and cloud security posture.
The benefits of the multi-cloud often triumph over the complexities, but it can certainly lead to many security risks. The lack of a centralized view of corporate data assets, sensitive data environment, and appropriate controls often challenges security teams.
Teams don’t have a complete view of sensitive data and where it exists. Additionally, each cloud service provider provides different security configurations. DSPM helps identify and mitigate cloud data security risks by helping teams analyze various parameters, including the visibility of sensitive data, its access control, data flow (data transformation), and infrastructure errors or misconfigurations.
Almost every industry is subject to some form of data privacy and security compliance, such as the National Institute of Standards and Technology (NIST), Payment Card Industry Data Security Standard (PCI DSS), or Sarbanes-Oxley (SOX). Compliance with national and international data protection laws like the GDPR or CPRA becomes more challenging. Every regulatory compliance has different requirements, which can be challenging without 360-degree insights into sensitive data.
For instance, PCI DSS doesn’t impose strict requirements for cross-border transfers of sensitive data. However, it does require entities to take appropriate security measures. However, GDPR imposes several strict restrictions concerning sensitive data transfer outside the EU borders.
Businesses subject to multiple regulations may find it difficult to categorize data as sensitive or personal, and depending on it, they may have to prioritize and establish security controls. DSPM provides visibility into the sensitive data and maps the data to different regulatory requirements. With appropriate tagging and classification, businesses can effectively ensure that appropriate controls are in place about security, cross-border transfer, and access policies and thus further establish compliance.
It provides complete visibility and control over an organization's data landscape. It enables the discovery and classification of sensitive data and security measures across multi-cloud environments, such as access controls and sanitization. With continuous monitoring of data access and usage, DSPM can detect unauthorized activities that threaten sensitive data, secure that data from potential breaches, and provide insights to help security teams optimize prevention strategies in the future.
DSPM continuously evaluates the security posture of data assets and AI applications by assessing risk scores based on identified vulnerabilities. This helps security teams prioritize and address the most critical risks first, reducing potential threats and improving overall data security.
DSPM further helps organizations reduce their attack surface by mapping data and AI flows and identifying weak points where data might be vulnerable due to misconfigurations, overprivileged access, and outdated security measures. Its ability to detect and automatically respond to security incidents helps organizations rapidly contain and remediate threats, reducing the potential impact of an incident on the organization and its data.
Businesses operating globally may find it difficult to categorize data as sensitive or personal per overlapping or conflicting compliance requirements. With appropriate tagging and classification, businesses can ensure that the right controls regarding security, access, and cross-border transfer policies are in place and establish compliance with various overlapping or conflicting regulations.
It is estimated that up to 74% of cybersecurity breaches are caused by human error. Mitigating the risk of public exposure of sensitive or personal data due to insider mistakes, misconfigurations, or inadequate security controls is essential. DSPM enables security teams to swiftly detect and correct misconfigured data assets, prioritizing those containing sensitive information. This prioritization helps minimize security vulnerabilities, breach incidents, and operational disruptions, maintaining a secure data environment.
Organizations are increasingly turning to AI learning models for enhanced operational efficiency and accelerated growth. However, Generative AI, such as large language models (LLMs), requires considerable data for training and fine-tuning. This introduces many risks, from sensitive data exposure to data poisoning or excessive agency. Advanced DSPM solutions help organizations safely embrace AI by providing capabilities like AI asset discovery, AI pipeline data flow security, and limited access entitlements.
DSPM enhances organizational agility by providing real-time insights into data security and enabling rapid responses to emerging threats. This allows organizations to adapt quickly to changes in the data environment. By having centralized control over data security policies, security professionals can ensure consistent enforcement across all environments, strengthening the security posture of the entire organization.
DSPM enables organizations to identify and eliminate redundant, obsolete, or trivial (ROT) data by providing comprehensive visibility into data usage patterns. This improved insight prevents costly overprovisioning while enhancing data lifecycle management and facilitating efforts to archive or delete outdated data, further reducing storage costs. Additionally, the continuous compliance monitoring capability of DSPM helps teams avoid costly fines and penalties associated with data breaches or noncompliance while reducing the manual effort required for auditing and reporting, further lowering costs.
DSPM provides a holistic approach to data security, integrating several key capabilities to ensure data management, compliance, and protection across diverse multi-cloud, on-premises, and hybrid environments.
GigaOm’s definition of DSPM begins with identifying sensitive data, which is the first fundamental step in understanding how DSPM works. The GigaOm Radar report further provides a detailed list of key capabilities a robust DSPM solution should offer.
Data discovery involves scanning and identifying all data assets within an organization’s data estate, including multi-cloud environments, on-premises systems, and hybrid infrastructures. DSPM solutions automate the process of locating structured and unstructured data assets, ensuring no data source is overlooked. This process helps organizations create a comprehensive inventory of what data they possess and where it is stored.
Once data is discovered, DSPM tools classify it based on its sensitivity, the regulatory requirements that pertain to it, its business importance, and according to policies relevant to the specific industry or internal policies determined by the organization. In the process of classification, the data may be tagged into categories like personally identifiable information (PII), financial records, or intellectual property (IP), as well as by regulations like GDPR, CPRA, Payment Card Industry Data Security Standard (PCI DSS), Sarbanes-Oxley Act (SOX), and Health Insurance Portability and Accountability Act (HIPAA). This critical step enables security teams to apply the right controls over the data and prioritize the protection of the most sensitive data.
Data flow mapping tracks how data moves within and between systems, applications, and networks. As data flows to and from various environments, tracking data movements and maintaining robust security measures becomes more challenging. Teams across the enterprise need to visualize how data moves between systems to accurately assess whether privacy and security controls apply consistently to the data. DSPM tools visually represent data flows, highlighting where data is accessed, transmitted, and stored. Understanding data flows helps teams trace data transformations, track duplicates for remediation, identify potential vulnerabilities more effectively, and ensure that security measures are applied consistently throughout the data lifecycle.
Once organizations identify, classify, and visualize data at rest and in motion, they need to analyze the data assets and flows to determine potential security threats and vulnerabilities. DSPM solutions enable organizations to conduct effective risk assessments by continuously monitoring data environments for vulnerabilities like unauthorized access and misconfigurations. DSPM tools can also assign risk scores to data assets, helping security teams prioritize remediation efforts and allocate resources to address the most critical risks.
DSPM monitors and tracks insights into sensitive data access based on users, roles, and geographies. Using sensitive data insights where data is mapped with regulatory insights, DSPM sets up access policies, such as which user or role can have what level of permission to access certain data, systems, or applications. Governance teams can effectively implement a least privileged access model by monitoring specific access parameters, such as inactive users or overtime access usage.
Building upon risk assessment capabilities, DSPM helps organizations enforce security controls to protect data based on its classification and risk scores. These controls may include access controls to restrict who is allowed to view or modify data, encryption to protect data in motion and at rest, and data masking to obscure sensitive information. By automating policies around these security controls, DSPM helps organizations ensure that the controls are applied consistently across all environments, reducing the risk of human error.
Data transformation occurs at any given instance, from creation and analysis to retention. Tracking data lineage at scale can be challenging for security teams, creating further security gaps. Robust DSPM solutions should allow data and security teams to track changes to the data over time to understand better how it is impacted, accessed, and changed down the line.
Continuous monitoring is essential for mitigating threats to sensitive data, determining what data might be at risk across systems, and spotting potential security issues in real-time before the data is compromised. DSPM comprehensively monitors data access, usage patterns, and security configurations, ensuring that any deviations are promptly identified. Additionally, it maintains detailed records of all data interactions in accordance with regulatory requirements for compliance.
DSPM tools can automatically respond to data breaches to mitigate their impact when they are detected. Automated response capabilities may include isolating the affected systems, revoking compromised access credentials, and initiating a breach notification process. In particular, DSPM assists in assessing the incident's impact by determining the amount of data exposed, identifying whose data was compromised, and evaluating potential regulatory fines. It also automates the required notifications as mandated by law while providing a comprehensive analysis to enhance security measures and refine response strategies for future threats.
A good DSPM solution should offer smooth integration with existing stacks, such as incident response tools, SIEM, etc. This important operational aspect ensures that the tool works seamlessly with existing workflows and helps maximize the current stack's value.
As data moves through various stages of AI development, it is exposed to multiple risks, ranging from sensitive data exposure and oversharing to poor-quality training data and excessive agency. DSPM solutions should provide advanced capabilities to organizations, enabling them to accelerate the safe adoption of AI, such as data sanitization, cleansing, redaction, and masking.
As organizations rapidly adopt cloud technologies, they face the challenge of securing both their infrastructure and their data across complex, multi-cloud environments. This landscape has given rise to two critical yet distinct security approaches: Cloud Security Posture Management (CSPM) and Data Security Posture Management (DSPM). While both practices involve continuous multi-cloud protection, they differ in focus.
CSPM emerged first, focusing on the infrastructure layer (rather than the data layer). Since DSPM technology is still in its early stages (Gartner categorizes the maturity level of DSPM as “embryonic”), it is common for some organizations to have difficulty distinguishing between CSPM and DSPM.
CSPM is a set of tools designed to discover, alert, and remediate cloud misconfiguration issues and compliance risks. Every cloud service has distinct settings, or configurations, that determine how it should be used. When teams move quickly in the cloud, they often configure services incorrectly, inadvertently increasing security risk. Each cloud provider and various security standards, like those by CIS or NIST, provide best practices to guide proper cloud service configurations. CSPM tools scan cloud infrastructure configurations against these best practices to identify and remediate security gaps immediately. Overall, CSPM tools primarily focus on cloud infrastructure, emphasizing a cloud-first approach.
However, CSPM solutions are limited because they lack context around the data stored in the cloud service. Without that context, it’s difficult for security teams to determine whether a configuration setting poses a security risk. For example, if an Amazon S3 bucket is publicly accessible through a configuration setting, a CSPM solution will always alert the user that it’s a security risk. However, if the S3 bucket contains non-sensitive data, such as marketing images for a website’s front end, then making the data publicly accessible is actually the correct behavior.
Due to their lack of intelligence around data, CSPM solutions can generate many false positive data security alerts, diverting security attention toward issues that don’t need to be fixed. When this happens, there is a risk that security owners or developers might ignore alerts, allowing a real misconfiguration, such as a public S3 bucket with sensitive customer PII, to slip through and increase the risk of a security breach.
DSPM complements CSPM with its deep intelligence around an organization’s data everywhere within cloud infrastructure services and SaaS applications. DSPM takes a “data-first” approach by prioritizing the discovery of sensitive data in the environment to identify potential security and compliance misconfiguration risks.
In the example above, a DSPM tool will only generate an alert if the S3 bucket contains sensitive data, such as customer PII, that should be protected based on company security policy. Besides identifying and auto-remediating security misconfiguration risks, a DSPM solution also helps establish data access control policies. Organizations can streamline their security, governance, and compliance functions with deep visibility into sensitive data and appropriate controls.
CSPM focuses broadly on all cloud services that provide computing, storage, and network solutions, ensuring they are configured correctly. DSPM tools focus broadly on all data systems and services within the cloud and SaaS applications ensuring these services are configured correctly while enforcing appropriate data access controls. Both solutions should be used simultaneously in an organization’s layered defense strategy.
Getting started with DSPM requires a structured approach that ensures effective deployment throughout your organization and seamless integration within your existing infrastructure. These steps are critical for building a unified and efficient data security environment that ensures continuous protection and compliance.
Identify Your Organization’s Security Requirements: Start by thoroughly understanding your organization’s security needs and objectives. Assess your data assets, compliance requirements, security policies, and the top risks to your sensitive data. Involve key stakeholders, especially from IT, compliance, governance, and legal teams, to gain alignment on your cybersecurity objectives from the beginning.
Select the Best Solution for Your Business Needs: After clearly understanding your security requirements, evaluate and select a DSPM solution that best fits your business needs. Consider factors like scalability, integration with other systems in your tech stack, breadth of security features, and customer support.
Empower Your Security Team to Work with the DSPM: Provide necessary training for your new DSPM solution, ensuring that key members of the organization understand its functionalities and how to leverage them effectively. Foster collaboration between your cybersecurity teams and other departments involved to integrate DSPM practices into your broader organizational workflow from the start.
Deploy and Configure the DSPM and Start Monitoring: Set up your DSPM technology according to your organization’s specific requirements and data environment. This involves configuring data discovery and classification processes, defining policies, setting up access controls, and defining monitoring parameters. Once deployed, initiate continuous monitoring to gather insights into your security posture and detect any potential threats.
Integrate the DSPM with Your Other Security Tools: Integrate DSPM into your existing security stack, which may include SIEM, IAM, and incident response tools (see the “DSPM Integrations” section below). Regularly updating and fine-tuning the DSPM setup based on feedback and evolving security needs will be necessary to maintain and optimize its effectiveness and value.
Identity and Access Management (IAM): DSPM integration enhances IAM security by enabling organizations to enforce least-privilege access to sensitive data. DSPM solutions can leverage IAM integration to understand identity attributes, such as user job role, location, and departments, to help define scalable attribute-based access controls.
Cloud Access Security Brokers (CASBs): CASBs control access to cloud systems, while DSPM offers more detailed information about the data within the applications, such as data sensitivity and usage. DSPM can complement CASBs to lead to more refined and effective security policies.
Security Information and Event Management (SIEM): DSPM enhances SIEM with the contextual data intelligence needed to correlate data-related events with other security logs. This offers a more complete view of potential threats and improves incident response capabilities.
Data Loss Prevention (DLP): DSPM provides accurate updates about where sensitive data is located, improving the accuracy of DLP policies and reducing false positives.
Intrusion Detection and Prevention Systems (IDPS): DSPM integration with IDPS improves the monitoring, detection, and prevention of intrusions that threaten sensitive data. This makes IDPS more data-aware and focused on protecting the most critical information
Security Analytics: DSPM feeds valuable data insights into security analytics platforms, enriching the analysis with detailed information about data sensitivity, access patterns, and potential risks. This allows for more sophisticated threat detection and risk assessment.
Rapid, Agentless Visibility into Critical Data: Ensure your DSPM solution provides agentless visibility into critical data across the entire environment. This capability allows you to quickly discover and map all data assets without the need for intrusive agents, enabling immediate insights and reducing complexities in the deployment process.
Centralized Dashboard and Reporting: A unified interface that aggregates data security metrics and generates comprehensive reports, simplifies monitoring, enhances decision-making, and ensures that all stakeholders have access to critical security information in real-time.
Continuous Detection and Prioritization of Critical Data Exposure: Ensure your solution can identify the most significant threats to your data security and enable efficient remediation efforts to protect sensitive data.
Data Lineage Mapping: Data lineage capabilities should be a core component of your DSPM solution. It enables data and security teams to track changes to sensitive data over time to better understand how and by whom it is processed. Security teams can identify gaps, detect unauthorized access, and establish optimal security policies.
Automated Remediation: Real-time remediation is a crucial feature to look for in your DSPM solution. The ability to automatically respond to security incidents as they occur minimizes the impact of data breaches and helps maintain the integrity and confidentiality of your data.
Automated Compliance Assessments: Automating your compliance assessment processes is critical for continuously adhering to regulatory standards. To simplify compliance management and reduce the risk of noncompliance violations or penalties, look for a DSPM solution that continuously evaluates your data security practices against relevant regulations.
Extend to AI: Choose a DSPM solution that extends its capabilities to generative AI-driven data environments. As GenAI systems handle increasingly sensitive data, the ability to apply DSPM principles to these environments is more critical.
Scalability and Performance: Large organizations with extensive data environments must have a DSPM solution that scales to accommodate growing data volumes while maintaining high performance. It should also consistently provide reliable data security management as the organization evolves.
Organizations seeking a DSPM solution should be aware of critical challenges that could hinder the tool’s implementation.
Organizations often have a myriad of teams, such as IT security, legal, and business teams, that operate in silos. This piecemeal data management approach can lead to significant data protection and compliance gaps. Since data security is a cross-functional responsibility, stakeholders from all key departments must collaborate to ensure the successful implementation of DSPM.
Another major challenge in most organizations is inconsistent data classification rules in different environments. Varying classification standards can result in significant errors and inconsistencies, impacting an organization's overall data security posture. For instance, a dataset tagged as "internal use only" in one environment might be labeled as "sensitive" in another, leading to inadequate access controls and sensitive data exposure. Organizations must seek DSPM solutions that work seamlessly across on-premise, hybrid, SaaS, and multi-cloud environments. This enables standardized classification and ensures consistent security policies and controls.
Organizations must not limit DSPM to classification only. Though data classification is critical, it is just a first step in the overall DSPM strategy. When organizations limit their DSPM strategy to only classifying data into personally identifiable information (PII) or financial data, it tends to fail when it comes to implementing broader security measures. DSPM should go beyond classification and include more comprehensive security controls like access intelligence and controls, real-time threat detection, or automated incident response.
False positives happen when a security tool marks a harmless event, action, or activity as a security threat. When DSPM tools are not tested for false positives and send such alerts, security teams may not trust the systems and ignore them. Consequently, genuine threats could go unnoticed. Organizations must test their DSPM solution for false positives at scale to overcome this mistake. Adequate testing will ensure that alerts are accurate and reliable.
Manual processes, especially concerning incident detection and mitigation, slow down response time, which could escalate security incidents. Organizations must consider automating remediation to deal with threats in real-time as they are detected to reduce manual effort and the risk of data breaches.
Despite the promise of DSPM technology, not all solutions are created equal. In its Hype Cycle™ for Data Security 2022 report, Gartner cites that having meaningful data insights and risk assessments is impossible if organizations continue to view different controls, such as sensitive data context, access governance policies, data transformation, and security configuration, through separate lenses. A lack of a centralized view will eventually create more security, governance, and compliance risks. Therefore, organizations must unify these controls into a comprehensive view of their data risks to establish effective data management and protection strategies.
Securiti’s Data Command Center replaces the fragmented Data Security Posture Management approach with a unified framework, providing deeper intelligence and visibility into an organization’s data landscape. This solution offers unified controls over data across all environments. Unifying data discovery, classification and cataloging, data lineage, access governance and control, and cloud security posture management enables teams to streamline their data obligations across security, governance, privacy, and compliance.
Securiti goes beyond typical DSPM solutions that support only the public cloud by delivering a solution that secures data across public clouds, private clouds, data clouds, and SaaS. It offers best-in-class DSPM capabilities by unifying intelligence around data (structured and unstructured, at rest and in motion), access governance policies and controls, data transformation insights, data mapping automation, and the ability to reduce misconfigured data systems.
In addition, Securiti helps organizations manage risk effectively in the unfortunate event of a data breach by automatically discovering impacted users, identities, and data.
Moreover, Securiti’s Data Command Center enables organizations to implement privacy and governance controls more intelligently without scanning and classifying data multiple times for each team (security, privacy, and governance). The siloed approach is cost-prohibitive and hampers team collaboration, making it impractical. With Securiti, organizations can unify their security, privacy, governance, and compliance controls into a common view, enabling a comprehensive understanding of their data risks and obligations.
Securiti stands out in the DSPM space as the #1 DSPM solution, as rated by GigaOm and Gartner Customer Choice report. Securiti’s approach to DSPM is integrated into the overall platform as a critical capability in a single, centralized, and comprehensive Data Command Center.
A company’s data security posture refers to its overall state of data security preparedness. Think of your organization’s data security “posture” as its “stance” for protecting your data landscape, especially the sensitive data within it. Much like a martial artist’s stance determines their ability to defend against an incoming barrage of attacks, your organization’s data security posture determines its strength and efficiency in fending off cybersecurity threats.
Gartner defines DSPM as a process that provides “visibility as to where sensitive data is, who has access to that data, how it has been used, and what the security posture of the data store or application is.” The solution helps improve sensitive data protection, risk assessment, incident detection and response, and regulatory compliance across various data environments, including private and public cloud systems, on-premises environments, hybrid infrastructures, SaaS applications, and more. This applies to both structured and unstructured data, as well as data at rest and data in motion.
Organizations operate in multiple cloud, on-premises, and hybrid data environments, making it increasingly difficult to gain a comprehensive view of their data everywhere and thereby protect it. DSPM addresses sensitive data protection in the cloud by finding and securing data everywhere, across all systems, for a unified approach and view of all data, including sensitive data. It takes a data-first approach to data protection (as opposed to an infrastructure-first approach like CSPM), drilling deep into the data to determine its sensitivity and vulnerability to risk and then protecting it accordingly.
DSPM works by finding and classifying all of an organization’s data across its entire data landscape, identifying where sensitive data resides, who has data access, and by whom it is being accessed. It continuously monitors the data, assesses the risk posed to it, determines risk scoring, detects vulnerabilities, prioritizes misconfigurations, and addresses compliance gaps in real-time. DSPM also helps organizations achieve regulatory compliance with detailed audit reporting and respond faster to potential threats and data incidents by providing real-time alerts.
To find the right DSPM tool for your organization, begin by assessing your specific needs. Your DSPM must offer the core capabilities of providing global data visibility into your entire data ecosystem, including on-prem systems, public clouds, private clouds, data clouds, SaaS and IaaS applications, data lakes, and warehouses. It should offer continuous data monitoring for risk assessment, providing actionable insights and remediation recommendations for sensitive data based on risk level. Your DSPM should offer robust access control features, strong privacy and compliance features tailored to your industry and location, seamless integration with the tools and technologies in your current tech stack, and the ability to scale for future data growth effortlessly.
Cloud Security Posture Management (CSPM) is designed to discover, assess, and remediate cloud misconfiguration and compliance risks. However, CSPM is limited because it lacks context around the data stored in the cloud service it protects. Without that context, security teams can find it difficult to determine whether a configuration setting poses a security risk. DSPM’s data-first approach drills down into the data assets themselves to provide deep data intelligence and context, reducing false positives and complementing CSPM solutions.
DLPs are good at detecting data being extracted from an environment. However, they are not good at data classification. DLP solutions use regex-based classification and generate classification labels that may not be accurate, resulting in false alarms about data being stolen. DSPM solutions can integrate with DLP to provide more accurate AI-based classification to help organizations get the most out of DLP.
The DSPM market is the fastest-growing segment of the cybersecurity industry and is increasingly considered critical for organizations to enhance their multi-cloud data security and compliance. In 2023, the market was valued at $94 billion and is projected to reach over $174 billion by 2031, showing a remarkable compound annual growth rate of 9.23% in that time.
The key components of DSPM include comprehensive data discovery and classification of all data across on-premise and multi-cloud environments for a unified, single view of sensitive data everywhere; data mapping and lineage tracking across data lifecycle; real-time monitoring, vulnerability scanning, and risk assessment of an organization’s data and security posture; risk remediation that includes automated risk scoring, security incident detection and response to quickly and effectively mitigate and address data risk; and compliance for hundreds of critical global regulatory requirements.
The right DSPM for your organization’s data environment should offer extensive and seamless integration with the rest of the tools, technologies, and data solutions in your tech stack, including those for access management (like IAM), data loss prevention (DLP), security information and event management (SIEM), cloud access security brokers (CASBs), and intrusion detection and prevention systems (IDPS).
In addition to the components mentioned above, organizations should look for rapid, agentless visibility into critical data, a centralized dashboard and reporting capabilities, continuous detection and prioritization of critical data exposure, data lineage mapping capabilities, real-time remediation, data exposure prevention, automated compliance assessments, extensibility to GenAI systems, and scalability to accommodate growing volumes of data.
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