The Evolution of Data Security: Why DSPM is the Future

As enterprises embrace AI and other data-intensive technologies, security is top of mind for every IT leader. Organizations today use enormous amounts of data to drive business growth, accelerate innovation, and remain competitive in the market. This is introducing new complexity and risk for security teams tasked with keeping sensitive data safe.

The industry is evolving from security solutions with limited data security capabilities to dedicated solutions that address the unique challenges of modern data security. In fact, Data Security Posture Management (DSPM) has emerged as an essential component of an enterprise security strategy, and has become the fastest growing security category.

In this article, we’ll discuss the challenges of modern data security, the evolution of DSPM, and how Cyera is helping enterprises adapt to changes in the security industry and growing data threat landscape.

Modern Data Security Challenges

Data security is crucial as businesses collect, generate, and leverage more data, especially with the widespread adoption of AI and machine learning. At the same time, data security has become more challenging as enterprises adopt hybrid infrastructure and their attack surface grows. Organizations are now challenged with protecting enormous amounts of data across unique environments, with the total amount of data set to reach 181 zettabytes this year.

In the past, enterprises adopted a wide variety of security tools — from data backup and recovery to endpoint security and data loss prevention — to improve their data security postures. In fact, it’s estimated that the average enterprise has assembled a portfolio of 130 products to protect its infrastructure, applications, and data. This fragmented approach still left security gaps and failed to protect enterprise data across SaaS, public cloud, data warehouses, and on-premises environments.

Legacy data discovery and classification tools often fall short because they fail to integrate across all environments and rely on manual methods to identify sensitive data. These visibility gaps create security blind spots that could expose organizations to costly data breaches. Inaccurate classification also wastes security resources and, even worse, leaves sensitive data unprotected.

Historically, many data security solutions focused on structured data like databases and transactional records because this type of data was more prevalent. However, generative AI is gaining popularity and relies on vast amounts of unstructured data for training and inferencing. The growth of unstructured data has introduced new obstacles for the accurate discovery, inventory, and classification of data that is needed to effectively define access controls for human and non-human identities.

In short, the IT landscape — and even the data itself — is constantly changing and evolving. Enterprises struggle to keep an up-to-date inventory of the data they have, and maintain an accurate understanding of their risk exposure. This lack of real time visibility and contextual awareness leaves many organizations at risk of regulatory compliance issues and makes it harder for them to safely monetize their data to remain competitive.

The Introduction of DSPM

The growing challenges and complexity of modern data security is pressuring the industry to evolve. Many enterprises are dissatisfied with their current security tools and recognize that traditional data security strategies are no longer enough to make data safely accessible for business use cases.

As data continues to proliferate across various platforms, a new category of DSPM solutions has entered the market to fill in the visibility gaps of legacy data security tools. DSPM originated as a data-centric extension of Cloud Security Posture Management (CSPM), focusing primarily on Infrastructure as a Service (IaaS) environments on public cloud platforms like AWS, Azure, and Google Cloud.

However, data is everywhere – in SaaS applications, on-premises servers, endpoints, and hybrid environments. The problem was that early DSPM solutions often lacked comprehensive support across multiple environments and struggled with scalability and accuracy.

DSPM vendors today are rapidly expanding their capabilities by integrating with existing security tools and frameworks to extend visibility and protection across the entire data landscape. DSPM ensures that there is security wherever there is data, whether it’s stored in a cloud service or an on-premises data center.

Many DSPMs also implement automated classification better than legacy data security tools. Rather than over relying on regular expressions, modern solutions use AI and machine learning to more quickly and accurately classify data. This reduces false positives while ensuring all sensitive data is properly identified.

Data security and privacy are also converging as organizations recognize the value of collaboration and shared responsibility between these teams. The in-depth visibility DSPMs provide is helping privacy teams translate complex frameworks into actionable policies that can be monitored and enforced.

DSPM is the Future of Data Security 

Although DSPM is a new category, it’s rapidly becoming a necessity to solve the challenges of modern data security. In fact, the 2024 DSPM Adoption Report found that 75% of organizations plan to implement DSPM by mid-2025.

The DSPM industry itself is also evolving rapidly, with modern solutions expanding from simple data discovery and visibility features to comprehensive data security capabilities. Effective DSPMs can now proactively assess and remediate risks based on contextual information. For example, a granular understanding of data enables security policies to be appropriately applied based on how and why an individual is accessing the data.

AI-powered data classification is also accelerating the value of DSPM because it helps determine the current risks of enterprise data and prioritize protective measures at scale. Using large language models (LLMs) and proprietary algorithms, advanced solutions can even learn and classify custom corporate data with a high degree of accuracy and precision.

DSPM is transforming other security practices by providing contextual insights about sensitive data as well. For example, innovative DSPMs are enabling real time incident response capabilities with accurate visibility into data exposures. This helps organizations to quickly understand the scope of a data breach and minimize its impact on the business.

Cyera for DSPM

As the data security industry evolves, partnering with a leading DSPM vendor like Cyera will be crucial for staying ahead of threats and maintaining a strong security posture. We’re the fastest growing data security company and continuously adapting our platform to meet the demands of modern data security. 

Cyera’s automated discovery and AI-powered classification capabilities deliver 95%+ precision and real time insights into data across all environments. By gaining an in-depth understanding of your unique data landscape, Cyera can apply the appropriate security measures to minimize risk without over-protecting non-sensitive data.

In addition, Cyera goes beyond a simple DSPM by providing a comprehensive data security platform that includes modules for data detection and response, privacy, compliance, data loss prevention (DLP), and more. This ensures enterprises can not just understand their data risk exposure, but also take action to effectively mitigate it.

By adopting a cutting-edge DSPM solution like Cyera, enterprises can navigate the complexities of data security with confidence and clarity. We strive to remain at the forefront of the trends reshaping the data security industry, and meet the security needs of enterprises now and in the future. 

Contact Cyera to learn more about staying ahead of growing data security threats with a cutting-edge DSPM solution.