You're evaluating DSPM tools. Every DSPM vendor promises complete visibility. Every demo looks impressive. Every sales deck claims their DSPM solution is different.

But most DSPM tools are fundamentally similar. They're scanners. They crawl your data stores, classify what they find, and generate alerts. Some DSPM tools scan faster. Some classify better. But they all share the same architectural limitations.

What is DSPM? At its core, data security posture management discovers sensitive data, classifies it, and monitors for policy violations. That's valuable. But it's not complete.

A 24/7 Data Defense Engineer is architecturally different. It doesn't just scan. It tracks, prioritizes, and provides actionable intelligence.

Here are 10 questions that separate basic DSPM tools from true data defense. Ask them when evaluating DSPM vendors.

Question 1: Can you show me data in motion, or only data at rest?

Why it matters: 65% of data security risks happen when data moves, not when it sits. If DSPM tools only show data at rest, you're missing most of your attack surface.
Scanner answer: "We scan data stores and can infer data flows from metadata."
Engineer answer: "We track actual data movement through APIs, pipelines, and services in real time with
‍Data Journeys™."
Red flag: If the demo only shows database contents and storage classifications, you're looking at basic DSPM tools.

Question 2: How do you handle source code visibility?

Why it matters: Data handling decisions are made in code. Without code visibility, DSPM tools only see the consequences of those decisions, not the decisions themselves.
Scanner answer: "We don't analyze source code directly. We focus on deployed infrastructure."
Engineer answer: "We analyze your codebase to see how applications handle data, what third parties receive data, and where sensitive information flows."
Red flag: If the DSPM vendor can't show you code-level data flow analysis, they're missing the earliest point where problems can be caught.

Question 3: What happens between scans?

Why it matters: If your DSPM tools run daily, that's 24 hours of blindness per cycle. Issues can emerge and cause damage before the next scan.
Scanner answer: "We offer hourly scans for higher coverage." Or: "We provide near-real-time scanning."
Engineer answer: "We monitor continuously. There is no between scans. We observe data flows as they happen, 24/7."
Red flag: Any mention of "scan frequency" reveals a point-in-time architecture. Real-time systems don't have scan intervals.

Question 4: How do you track AI and ML data flows?

Why it matters: AI systems create unique data security challenges. Training data lineage, model inputs, inference outputs, and vector databases all need governance.
Scanner answer: "We can scan AI model storage and vector databases."
Engineer answer: "We track the complete AI data lifecycle: training data sources, data transformations, model inputs, inference outputs, and embedding storage. Continuously."
Red flag: If AI governance is positioned as a future roadmap item or separate add-on, the DSPM tools weren't built for it.

Question 5: Can you trace a data breach back to its source?

Why it matters: When incidents happen, you need to understand the complete breach blast radius. Where did the data come from? How did it get exposed? What else might be affected?
Scanner answer: "We can show you what sensitive data was in the compromised system."
Engineer answer: "We can show you every system that data touched, when it arrived, where it went, and what transformations occurred. Complete lineage."
Red flag: If the DSPM tools can only tell you what data was exposed but not how it got there, incident response will be painful.

Question 6: What do you do when you find an issue?

Why it matters: Detection without action creates alert fatigue. DSPM tools that only find problems and wait for humans don't scale.
Scanner answer: "We generate alerts that integrate with your ticketing system."
Engineer answer: "We prioritize issues by actual risk and business context, provide actionable remediation guidance, and give your team the complete information they need to resolve issues quickly. Human judgment stays in the loop, but investigation time drops from hours to minutes."
Red flag: If every issue becomes an undifferentiated alert requiring manual investigation from scratch, your team will drown as your data footprint grows.

Question 7: How do you handle third-party data flows?

Why it matters: Data leaving your environment to vendors, partners, and SaaS tools represents significant risk. You need visibility beyond your perimeter.
Scanner answer: "We scan your internal data stores. Third-party visibility requires additional integrations."
Engineer answer: "We track data flowing to third parties through API calls, SaaS integrations, and data exports. We map your complete vendor data exposure."
Red flag: If the demo doesn't show data leaving your environment, you're only seeing half the picture.

Question 8: What's your detection-to-response time?

Why it matters: Security is a race against time. The faster you detect and respond, the smaller the impact.
Scanner answer: "Detection happens at scan time. Response depends on your team's SLA."
Engineer answer: "Detection is continuous. We surface issues with full context and recommended actions immediately, so your team can respond in minutes rather than days."
Red flag: If detection depends on scan schedules, response times have a floor you can't improve.

Question 9: How do you handle shadow data and shadow IT?

Why it matters: Shadow data and shadow IT represent unknown risks. Data copied to unapproved locations. SaaS tools adopted without security review. AI services connected without governance.
Scanner answer: "We discover data in known data stores. Shadow IT discovery requires separate tooling."
Engineer answer: "We detect unknown data flows to new destinations, shadow AI usage, and ungoverned SaaS connections through continuous monitoring."
Red flag: If the DSPM tools only find what they're configured to look for, shadow risks will stay in the shadows.

Question 10: What happens at 3 AM on Saturday?

Why it matters: Data security issues don't follow business hours. Neither do attackers.
Scanner answer: "Scans run on schedule. Alerts go to your on-call team."
Engineer answer: "Our 24/7 Data Defense Engineer monitors continuously. When critical issues emerge at any hour, it surfaces them with full context and recommended actions so your team can respond quickly and confidently."
Red flag: If the answer is purely "we alert and you respond with no additional context," you're buying DSPM tools that work business hours while threats work around the clock.

Scoring your evaluation

After asking these questions, you'll have a clear picture of the DSPM vendors you're considering.

Most scanner answers: The DSPM tools provide point-in-time visibility into data at rest. Useful for compliance snapshots and data cataloging. Limited for active security.
Most engineer answers: The DSPM solution provides continuous visibility into data in motion. Capable of tracking and prioritizing issues with full context. Built for modern data security.
Mixed answers: The DSPM vendor may be transitioning architecture or adding capabilities. Dig deeper on roadmap versus current functionality.

The right choice depends on your needs. If you only need periodic compliance reporting, basic DSPM tools might suffice. If you need continuous protection for data flowing through cloud-native architectures, AI systems, and third-party integrations, you need a 24/7 Data Defense Engineer.

Your data doesn't wait for scans. Your DSPM shouldn't either.