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Thinking About DSPM? 8 Crucial Considerations Before You Buy

Author: Zach Luze, TBDCyber CISO and Director of Data and Security Architecture



Data Security Posture Management (DSPM) is generating buzz with its scalability, advanced classification, and broad coverage. But buying a DSPM solution isn’t a plug-and-play decision—it requires careful evaluation. Here’s what I tell clients to consider before investing.


1. Know what DSPM does– and doesn’t– do

DSPM identifies where sensitive data lives, highlights vulnerabilities, and prioritizes risks. However, it rarely remediates issues directly. Like vulnerability management, DSPM requires your team to engage with owners to remediate identified issues (e.g., exposed sensitive data, misconfigured storage, or public access risks). If your team isn't practiced at engaging others to drive remediation, you may struggle to realize value from DSPM.


2. Define use cases

“Discovering sensitive data” is not a use case—it’s a feature. To get real value, define how DSPM will support security goals, such as:

  • Prioritizing and remediating data-related vulnerabilities

  • Enhancing existing security processes with DSPM insights

  • Identifying sensitive or regulated data where it should not exist and engaging data owners and custodians to remove or migrate it

Clear use cases ensure you choose the right solution.


3. Best practices are being invented

DSPM is still an emerging field, and “best practices” are evolving. Vendors will not provide a step-by-step guide to success. Expect an iterative process—facing roadblocks, adapting workflows, and finding unexpected DSPM use cases along the way.


4. Beware of bolt-on DSPM

Every data security and privacy vendor is adding DSPM, but not all solutions are created equal. Many are bolt-on to existing products with weak functionality. A true DSPM should be purpose-built, not an afterthought.


5. Classification accuracy is paramount

DSPM prioritizes risk based on data sensitivity and vulnerability severity, so if classification is weak, prioritization fails.

Some solutions rely solely on REGEX-based classification, primarily for PII data, which often leads to false positives. Others baked in large language models (LLMs) long ago, reducing false positives and expanding the catalog of identifiable data to data types of legacy identifiers struggle to catalog. For most organizations, yesterday's classification capabilities are not going to cut it.


6. If it’s not integrated, you won’t see it

DSPM only scans the cloud and SaaS environments you integrate. It will not find shadow tenants (e.g., rogue Azure or AWS tenants or accounts). To uncover shadow tenants and instances, you will need an inline CASB or a SaaS discovery and control platform (e.g., Grip Security).


7. Ignore the quadrants

Some have sent me Gartner-style maturity quadrants for DSPM solutions. A word of warning: none are credible, and I doubt the writers have hands-on experience with the solutions.

Conduct your DSPM selection internally or partner with a trusted advisor – don’t let a quadrant dictate your decision.


8. Navigability over fancy visuals

A console's heat maps and bubble charts may look impressive during a demo, but in practice, teams often rely on Excel, Tableau, or PowerBI for generating metrics and dashboards.

Focus on navigability. DSPM probably will not be anyone's full time job, so an intuitive interface for answering critical questions (which assets store SSNs, what are the vulnerabilities of each, what are the identities with access, etc.) is essential. The more cumbersome the interface, the more likely your DSPM becomes shelfware.


In summary: DSPM can be transformative—if you choose wisely

DSPM isn’t a silver bullet, but it can be a game-changer when approached thoughtfully. Ask hard questions, demand real proof, and plan for heavy lifting.


If you’d like to learn more or need assistance with any aspect of your data security or privacy programs, reach out—TBDCyber would love to chat!

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