What is DSPM?

Data Security Posture Management (DSPM) is a security approach that enables organizations to continuously monitor, access, and secure sensitive data across both cloud and on-premises. It provides visibility into where the critical data is located, who can access it, and how it is being protected.

How DSPM Works in the Real World

Some practical examples of DSPM are 

1. When a health care provider integrates with DSPM, all the patient’s medical records and their insurance claims can be found. They will be categorized under Protected Health Information (PHI) and regulated. 
   Depending on individual sectors like accounting, marketing, and intellectual property, they can classify the data based on its types. That is finding all the data and categorizing it. 
2. A data map shows whether an application has unnecessary access to a database, and DSPM detected it with ease. DSPM visualizes and shows how the data is mapped across all applications.
3. When a high-risk folder is shared with any sensitive data, DSPM  automatically alerts the owner and restricts access unless it is modified. Thereby detecting the potential risks and warning the users.
4. DSPM triggers an alert when an unauthorized person tries to access the database. It ensures that only authorized person has access to keep data secure.
5. In real time, before going to an audit for HIPAA, DSPM provides a clear report showing where the data is stored and verifies that all necessary encryption has been done. It continuously monitors and gives feedback.

Core Capabilities of DSPM Solutions

The core functionalities of Data Security Posture Management (DSPM) can be grouped under five basic stages.

1. Discover data and classify it: DSPM solutions integrate all environments such as Cloud, SaaS applications, and On-premises and automatically detect the data. 
   Now that data is detected, it is not enough to protect it; we need to classify it. It can be done based on sensitivity. Information such as Personally Identifiable Information (PII), financial data, and Protected Health Information (PHI), etc. This is important because it prioritizes what needs the most protection.‍
2. Mapping data flow: DSPM tracks how sensitive data moves between different components in the organization’s servers, applications, and databases. This highlights the weak points and shows where the data is vulnerable.‍
3. Risk detection and Rectification: By analyzing data classification and its flow, DSPM identifies risks such as unauthorized access and data leakage. It highlights the critical issues based on the sensitivity of data.
   Now that risks are identified, DSPM provides recommendations and automatically rectifies them if needed. Some remediations are like specifying steps to modify IAM policies in AWS and modify sharing settings in Google Drive. 
   In some cases, DSPM automatically triggers alerts for misconfigurations, unauthorized access, or any regulatory violation that is noted.    ‍
4. Security Posture Management: Data Security Posture Management (DSPM) helps organizations to implement appropriate security controls such as firewalls and encryption. 
   By establishing clear policies and procedures, any intentional and human errors for data breaches can be avoided. It regularly analyzes data access permissions, encryption status, and data exposure.‍
5. Monitoring and Compliance Management: DSPM continuously monitors the access controls in real-time and alerts when any deviation is met. It maintains auditable logs and generates reports. DSPM solutions help organizations to meet regulations such as HIPAA and GDPR by giving proper data visibility.

DSPM vs. CSPM, DLP, and CIEM: What's the Difference?

DSPM, Cloud Security Posture Management (CSPM), Data Loss Prevention (DLP), and Cloud Infrastructure Entitlement Management (CIEM)  all sound similar in terms of security, with some differences in their main focus, core functionality, where they operate, and what it does not do.

DSPM

• It mainly focuses on data security posture.
• Its core functionality is discovering the data, classifying and monitoring it, and providing automated suggestions.
• It operates in both on-premise and cloud environments.
• It does not focus on the movement of data and infrastructure settings like DLP.

CSPM

• It mainly focuses on cloud security.
• Its functionality is to identify misconfigurations, vulnerabilities, and compliance issues in a cloud environment.
• It operates on public cloud platforms.
• It does not focus on data and its access platforms.

CIEM

• It focuses mainly on user identities and their permissions in the cloud.
• It prevents privilege misuse.
• It operates on cloud platforms.
• It does not focus on data security or content like DSPM.

DLP

• It mainly focuses on how to prevent data loss.
• It focuses on movement and leakage prevention.
• It works in endpoints, networks, cloud, and SaaS.
• It does not focus on data visibility or misconfigurations.

Key Benefits of Implementing DSPM

DSPM is gaining importance due to the following benefits

• Multi-cloud and Hybrid Environments: Data is scattered across all environments, either on-premises, cloud, or hybrid infrastructure. DSPM pulls the data from all places and gives us a complete picture, ensuring protection and compliance.
• Data visibility: Due to large volumes of data, we don’t exactly know where the data is coming from. It has become a challenge to manage all the data. DSPM gives clear visibility into data assets, which helps organizations to monitor, classify, and protect data effectively.
• Shadow Data: We create data backups that often go unnoticed. DSPM helps to find and fix this duplicate data, thereby saving space in a cloud environment.
• Data breach: Data breaches are increasing day by day due to hackers. Data Security Management spots the data leaks and makes them secure with regulations.
• Gains customer’s trust: Knowing where the data is stored and that it is secure has helped the organization to gain trust from the customer.
• Continuous monitoring: Posture Management watches every move of your data, does continuous inspection and not just a one-time security audit, from where it lives, to who can see it, and how it is being used.

Common Challenges and Mistakes in DSPM Implementation

Some common challenges/mistakes faced by an organization while implementing cloud DSPM solutions are

• Deploying DSPM without clear objectives will not give full security for data. 
• Data is widely spread across multiple clouds, data lakes, and SaaS platforms, which gives limited data visibility and raises Complexities in classification.
• Human error and over-permissioned access lead to more data breaches.
• Compliance with HIPAA and GDPR requires more data control and transparency.
• Legacy tools like DLP or CSPM do not provide full data visibility, and integration with them becomes difficult.
• Sometimes, unsanctioned cloud services or applications can handle sensitive data and can lead to shadow data. Handling that becomes difficult for DSPM solutions to find unmonitored assets.
• Implementing DSPM without strong support from stakeholders and the necessary teams will create hurdles.

Getting Started with DSPM at Scale

Implementation and management of Data Security Posture Management solutions across various platforms involves careful planning, stakeholder engagement, and automation. A successful deployment will require a basic steps to be followed.

1. Identifying DSPM objective and goals: To begin, create a list of data types(structures, unstructured, or semi-structured) in all environments (cloud and on-premises). Understand that the key objective of implementing DSPM is to reduce overexposure, avoid data breaches, and align with standard regulations.
2. Discover and Classify sensitive data: Find and prioritize critical data assets and high-impact use cases. Use DSPM tools to automatically identify shadow data, abandoned stores, and data that is present in legacy systems. Categorize the data based on its sensitivity levels (eg, public, internal, and restricted).
3. Establish security policies and prioritize: Identify and establish user access and their permissions based on role-based Access controls. Set up security contacts and notify data owners when risk is detected. Automate least privileged policies to ensure that users have required access for the functions. 
   Regularly review and update data classification policies and access governance rules with respect to DSPM solutions and make sure that they align with business requirements.‍
4. Monitor and remediate: Continuously monitor data movement, changes in data flow, its access, and potential threats using DSPM tools. Ensure all new systems and cloud accounts are automatically enrolled in DSPM insights.‍
5. Integrating DSPM with existing frameworks: Integrate DSPM with existing security frameworks and tools such as 

• SIEM/ SOAR- for centralized logging and automated incident response, 
• IAM/CIEM - for getting a complete picture of access controls and least privilege enforcement.
• DLP/CSPM - for workflow automation and data leakage prevention.

6. Training and awareness: Invest in training employees in ensuring data security best practices, how to use the DSPM tool, data handling procedures, and adhering to security policies. 
7. Scale and evolve: Utilize DSPM’s automation features to remediate common misconfiguration problems with any change in performance. Track the total number of sensitive data assets, how much will be exposed to risks, and the time to solve those.

Why DSPM is Mission-Critical in 2025 and Beyond

DSPM is mission-critical in 2025 due to increasing data threats and complexities. Key reasons why DSPM is unavoidable  include:

• Cloud complexity: Organizations now operate in a multi-cloud environment, with SaaS applications. As the data volume increases, it will become more complex to handle, manage, and implement effective controls on the data. DSPM can detect abnormal user behavior and access patterns, and it identifies insider threats.
• Frequent cyberattacks: According to the statistics, cybersecurity attacks and data breaches have increased rapidly in 2025. DSPM solutions are critical in providing proactive, risk-based data protection. 
• AI and DevOps: Generative AI and Large Language Models (LLM) will transform business operations and also bring new security threats. DSPM is the only solution that identifies where the sensitive data is being fed into AI models, and who can control the access and ways to protect the sensitive data. 
  DSPM can integrate with DevOps workflows, identifying and resolving the data security issues in the development process.‍
• Least Privilege: Over-privilege is becoming more common and generates data breaches. DSPM automates data access intelligence and enforces least privilege by mapping user details and their access. It identifies dormant accounts and provides actionable recommendations.‍
• Enhancing compliance and governance: DSPM will impose strict regulations, support continuous monitoring, and reduce manual audits, thereby securing the data with respect to HIPAA and GDPR.

Why Choose Entrans for DSPM?

Data is the most valuable and vulnerable asset; protecting it is a continuous and dynamic process. To keep track of critical data and ensure that it is safe, use DSPM. DSPM is no longer optional; it is a key initiative for managing escalating data risks, supporting compliance, and enabling resilient business operations in a data-driven world. 

Implementing DSPM at scale can be complex; it requires technical expertise, strategy, and the right data security management posture vendor. Entrans brings the expertise, tools, and required ongoing support to do that. 

• We have tailored DSPM strategies to align with business requirements. 
• Our team has a proven record in delivering scalable and secure data solutions across various industries.

Choose DSPM to stay secure and scale with confidence. Choose Entrans to achieve it faster. Want to know more about. Book a consultation call with us to secure your data and be sustainable.