DSPM vs Legacy Data Security Tools

Your sensitive data is at risk, but it’s not the cloud’s fault.

According to research by Forrester, 74% of security decision-makers estimated that their organization’s sensitive data was breached at least once in 2022. Data breaches have also gotten more expensive, costing $4.45 million on average. 

Many vulnerabilities go unnoticed because companies are trying to secure modern cloud environments with data security solutions built for on-prem data. Legacy data security technologies don’t see all of your sensitive data, create high upfront costs, and are manual to operate and maintain that they end up underused and not correctly configured. 

Forrester’s research quoted above also finds that the top three data security challenges faced by organizations right now are:

1. Cumbersome manual processes, including having to connect data security solutions to specific data sources.
2. The time it takes to implement data security technologies and see value.
3. The management headache that comes with using solutions that create fragmented security controls across different on-prem/cloud environments.

These problems happen when you try to secure data in the cloud era with legacy data security tools. There is a better way. 

4 Challenges with Legacy Data Security Tools

Some of these tools are based on technology that, on a fundamental level, has stayed the same for over 15 years. Legacy data security tools were not designed for the cloud era where data is increasingly scattered, complex, and stored across diverse environments.  

1. Partial visibility of data. Legacy tools are often designed for one type of data and not the other. For example, some focus only on unstructured data, while others focus mostly on structured data. Many do not connect to SaaS, meaning that becomes a blindspot or is covered by another tool. As a result, teams that rely on these tools may find themselves with siloed visibility of only subsets of data, depending on the type of data and where it’s located.

2. Slow time to value. Data security is an immediate concern. Legacy systems take months and years to realize value. This results in prolonged deployment process, operational bottlenecks, and expensive resourcing requirements via professional services and dedicated specialists. 

3. False positive classifications. These tools over rely on regular expressions (RegEx) to classify data. This means dedicated resources need to spend time manually writing rules, tuning them, and validating the accuracy of the classification outputs. Because they rely on static rules and require manual validation, legacy tools generate a lot of false positive classifications. 

4. Overhead to manage. Legacy data security tools were designed when most data was stored on-prem, requiring the use of agents and dedicated resources to maintain connections to various datastores. This requires users to deploy both hardware and software with separate architectures, depending on the location of data.

Modernizing your Data Security Approach with DSPM

Data Security Posture Management (DSPM) is a solution made to solve modern data security challenges.

Unlike legacy data protection solutions, DSPM is a cloud-native data security technology. It allows security teams to harness the ease and speed of the cloud via APIs that seamlessly connect to IaaS, SaaS, and PaaS environments. There are no manual connections to manage or a list of access details to keep updated for each and every datastore. 

DSPM can understand your data estate in a matter of hours to days and start giving you real-time insight into data security risks that expose data as a result of datastore misconfigurations, overly permissive access, or lack of security controls around the data. 

Covering your entire data estate, DSPM enables security teams to view sensitive data across silos via a single pane of glass. A good DSPM solution should be able to understand structured and unstructured data, no matter where the data is located including in on-prem environments.  

DSPM that leverage AI can classify data with a very high degree of accuracy, as well as generate relevant context about that data to help security teams enforce approach controls. For example, context will tell you if your data is about a customer or employee, if the data is encrypted or exposed as plaintext, and if the data is about a French or US resident. 

DSPM vs Legacy Data Security Tools

Choosing A DSPM Solution For Your Needs

When Forrester asked over 250 security decision-makers what technologies would make the most transformational differences, the top three needs were dynamic security controls (81%), real-time exposure detection (76%), and data security posture management (72%).

Meeting these requirements and going beyond them is possible with a solution like Cyera’s AI-powered DSPM solution. 

With Cyera, you can:

• Provide instant visibility into data. This means your datastores, data classes, and data exposures are understood in hours to days, rather than months to years. 
• Connect to your datastores with a single IAM role. This is possible because Cyera’s cloud-native approach is fully agentless, unlike legacy architecture, which requires manual connections to every datastore. 
• Continuously discover all of your data across environments.
• Leverage AI-powered classification for highly accurate outputs. 
• Flag sensitive data everywhere it exists and highlight exposures. This includes data stored in SaaS, IaaS, PaaS, and on-prem. 
• Automate remediation for tasks like applying encryption to data at rest and ensuring correct logging and auditing is configured.

Schedule a demo with Cyera to see how a cloud-native DSPM solution can give you the data visibility you need to secure your data.