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Converging DSPM, DLP, and Data Privacy

May 29, 2024
Cyrus Tehrani
5 min read

If you spend any time reading about data security, you already know that data breaches are commonplace and privacy regulations are tightening. However, our collective understanding of data security tools and solutions that address these challenges can probably use a boost. For example, many of us have heard about Data Security Posture Management (DSPM), Data Loss Prevention (DLP), and Data Privacy.

But whether you’re familiar with only one of these pillars of data security or all of them, it’s important to explore their similarities, differences, and how they converge.

This post explores how these three critical domains intersect, their unique roles, and the synergies they create for data security and privacy.

A brief primer

Let’s start with a brief overview of these data security pillars.

Data Security Posture Management (DSPM)

DSPM focuses on assessing and managing the security posture of an organization’s data. It’s about understanding where sensitive data resides, who has access to it, and ensuring it’s used appropriately. The integration of AI and Machine Learning in DSPM has revolutionized its capabilities, offering predictive analytics and enhanced data security strategies.

Data Loss Prevention (DLP)

DLP plays a crucial role in protecting sensitive data from leaks and unauthorized access. The goal of DLP is to prevent data breaches and also ensure compliance with various regulatory requirements. DLP tools are increasingly common and sophisticated, capable of identifying, classifying, and protecting sensitive information across ever-expanding cloud environments.

Data Privacy

While the concept of Data Privacy is essentially self-explanatory, keeping up with it is increasingly challenging. With regulations like GDPR and CCPA, organizations must ensure transparency and protection of personal data. The cost of non-compliance is high, making efficient discovery and protection of sensitive data a crucial part of doing business — especially when customer trust and the bottom line are at stake.

Convergence of DSPM, DLP, and Data Privacy

When organizations bring DSPM, DLP, and Data Privacy together, it can bring about a strategic alignment that addresses comprehensive data protection in a nuanced and layered way. Their convergence transcends a mere combining of different technologies and can foster a cohesive strategy that leverages the strengths of each domain to enhance overall data security and compliance.

Let’s discuss three key benefits for converging these data security pillars:

  • Enhancing security
  • Achieving real-time data protection
  • Boosting regulatory compliance

Enhanced security

DSPM’s ability to identify and assess data risks is complemented by DLP’s functionalities for prevent data breaches. For example, if DSPM identifies a set of sensitive data as high-risk due to its accessibility, DLP can immediately enforce policies to restrict unauthorized access or sharing.

Both DSPM and DLP play critical roles in helping promote the third pillar, Data Privacy. DSPM assesses how data is stored and accessed to ensure it aligns with privacy standards, while DLP enforces rules that prevent data from being shared or accessed by unauthorized parties. Combined, they can help maintain compliance with privacy laws.

Real-time data protection

As data moves through an organization’s systems (creating data sprawl), DSPM continuously monitors and evaluates its security posture, while DLP dynamically applies policies to protect data in real-time. This integrated approach ensures that sensitive data is consistently protected, regardless of its location or how it’s being used.

Enhanced regulatory compliance

With various global privacy regulations, organizations can’t escape the increasingly complex compliance landscape. DSPM provides visibility into data storage and access patterns, while DLP ensures that data handling meets specific regulatory requirements.

This synergy is crucial for maintaining compliance in the ever-evolving regulatory environment.

The importance of data classification

At the heart of DSPM, DLP, and Data Privacy lies a fundamental process: data classification. This critical step is what enables organizations to apply the right level of protection to their data, based on its sensitivity and the regulatory requirements it falls under. Without accurate data classification, the effectiveness of DSPM, DLP, and Data Privacy initiatives can be significantly limited.

For DSPM, data classification provides the groundwork for identifying which data assets require more stringent security controls. By classifying data from public to highly confidential, DSPM solutions can prioritize risks and assign security measures accordingly.

DLP also relies heavily on data classification to enforce policies effectively. By understanding the classification of data, DLP tools can apply the appropriate policies to prevent unauthorized access or sharing, ensuring that only the right people have access to the right data at the right time.

When it comes to Data Privacy, classification is key to compliance. Knowing which data is personal or sensitive according to various regulations allows organizations to apply specific privacy controls and manage consent, access rights, and breach notifications more efficiently.

Knowing their role

While there is significant overlap in the objectives of DSPM, DLP, and Data Privacy, each brings unique capabilities to the table.

Here’s how you can think about each role.

DSPM: Data security architect

DSPM offers a bird’s-eye view of an organization’s data landscape. It identifies where sensitive data resides and how it’s being used, providing crucial insights for strategic data security planning. By evaluating the security posture of data stores and access patterns, DSPM helps organizations prioritize risks and allocate resources effectively.

DLP: Data protection enforcer

DLP is more hands-on, applying specific policies to prevent unauthorized access and data leaks. It acts on the insights gained by DSPM to enforce data security at a more granular level.

DLP tools are designed to detect and respond to data breaches in real-time, offering immediate protection against data loss.

Data Privacy: Regulatory guardian

Data Privacy frameworks ensure an organization’s data handling practices align with legal and regulatory requirements. Data Privacy often includes managing consent, data subject rights, and breach notification. Remember, Data Privacy is not just a technology issue but involves legal, compliance, and business units, ensuring that data handling aligns with both internal policies and external regulations.

Working better together

The convergence of DSPM, DLP, and Data Privacy creates a robust defense mechanism against data breaches and compliance violations. By integrating these three domains, organizations can ensure that their data security strategies are reactive but also proactive and strategic. This integrated approach should lead to a more resilient and compliant data management framework, capable of adapting to new threats and regulatory changes.

What if you could streamline these three critical elements with a single, powerful solution? Concentric AI offers that power: a unified platform that embodies the best of all three worlds.

Contact us to book a demo today to see — with your own data — how you can boost your data security posture, enforce your protection strategies, and maintain regulatory compliance with best-of-breed ease and efficiency.


Libero nibh at ultrices torquent litora dictum porta info [email protected]

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