Data security management used to be a behind-the-scenes task, handled quietly by IT teams while the rest of the company did their thing. Not anymore.
Today, with data sprawled across cloud apps, on-prem servers, personal devices, and third-party platforms, keeping it all secure feels like trying to babysit a dozen toddlers in a room full of glue, glitter, and permanent markers.
The risks are real. One wrong move, one missed misconfiguration, and suddenly you’re the star of the next news headline.
Yet, most companies still struggle with the basics, like knowing where their sensitive data lives, who has access to it, and whether it’s being quietly copied to someone’s personal Dropbox at 2 a.m.
In this guide, we discuss the top five biggest challenges organizations face when it comes to data security management and how to handle them without turning your IT team into a 24/7 crisis response unit.
1. More sophisticated cyber threats
The challenge: Cyber threats are getting sneakier. Gone are the days of easily identifiable viruses. Today’s hackers use more sophisticated ransomware, phishing scams, and social engineering to access your sensitive data. It’s like playing whack-a-mole. Blindfolded.
The solution: AI to the rescue! If you’ve ever wished for a superhero that could detect threats before they happen, AI and machine learning are pretty close. They can analyze patterns in your network and flag anything unusual, like a bad actor trying to download 10,000 files at 3 o’clock in the morning. The best part is, unlike your overworked IT team, they work 24/7.
Best practice: Get ahead of the game by implementing automated monitoring systems with user behavior data analytics. Let the machines handle the routine work so your team can focus on the stuff that matters.
2. Data privacy and compliance regulations
The challenge: Remember that time you had to sift through a 10-page user agreement before hitting “Accept” on an app? Now imagine that, but instead of just agreeing to terms, you have to stay compliant with a whole mess of regulations, like GDPR, CCPA, and HIPAA where the terms are way more complicated. If you’re not compliant, let’s just say it could cost you more than just the numbers on the bottom line.
The solution: Compliance management, FTW. You can’t afford to miss a step with any of these regulations. Thankfully, there are compliance management tools that automate tracking and reporting of the regulations and their controls. They can scan your data, flag anything that may be at risk and needs attention and even prepare reports for audits.
Best practice: Automate your compliance tracking. Audit often. It’s that simple.
3. Data sprawl and data silos
The challenge: You’re probably familiar with the chaos of scattered data—files here, there, and everywhere. In the cloud, on-prem, structured, unstructured… Without a unified view, your team is left to play the not-so-fun game of data detective, trying to figure out where the critical information is hiding. It’s like trying to find your car keys but there are 23 different drawers and none of them are labeled.
The solution: Data categorization, classification, and centralization are key. A good data classification strategy can help you organize and prioritize data, so it’s easy to find when needed. Once you’ve classified your data, it should be centralized in one secure, easy-to-manage location.
With a strong data security governance platform, you gain visibility into your data security posture. Instead of hopping between multiple tools and dashboards (which, let’s be honest, is the adult version of herding cats), you can have everything in one place with a 360-degree view of your data’s health and security.
Best practice: Use data security governance frameworks to create a standardized approach across your organization. Pro tip: don’t try to herd cats — that expression was coined for a reason.
4. Insider threats
The challenge: You trust your team, but sometimes people make mistakes, or worse, they act with malicious intent. Insider threats—whether intentional or unintentional—are sneaky and can cause serious harm to your company’s data security. It’s like leaving your front door unlocked because you “trust” everyone in your neighborhood.
The solution: Least privilege access and user behavior data analytics make a dynamic duo. By giving employees access only to the data they need for their job, you reduce the risk of accidental or malicious data exposure. Think of it like giving your roommate a key to the house but not the safe in the basement that has your Michael Jordan rookie card. Least privilege keeps everything secure, and everyone has what they need.
But sometimes, the best way to catch an insider threat is by spotting unusual behavior. Are your employees suddenly downloading files they’ve never touched before? Or accessing data outside of normal work hours? User behavior data analytics helps you spot these red flags before they cause damage.
Best practice: Regularly review user access controls and set up alerts for any unusual behavior. And lock up the basement just in case.
5. Secure data sharing and collaboration
The challenge: Data sharing is important for productivity, but it’s also risky—especially when you’re sharing sensitive information with partners, vendors, or even remote employees. Employees share sensitive data way more often than you think and in more ways than you’d imagine. The risk of that data being leaked is real: it’s like passing a secret note in class and hoping the person who reads it isn’t forced by the teacher to share with the class.
The solution: Data loss prevention (DLP) tools minimize the risk. DLP tools help monitor and control what data can be shared and with whom. Like an unstoppable bouncer at the door of your data club only letting in the VIPs, they’re your data’s security guard, making sure sensitive information doesn’t slip through the cracks.
Best practice: Use DLP tools and end-to-end encryption for any data that leaves your organization. And of course, don’t share your secrets with just anyone.
Are Data Security Management and DSPM the Same Thing?
Short answer: Not quite, but they’re closely related.
Data security management is a combination of policies, tools, and practices for protecting sensitive data, ensuring compliance with regulations, and managing risks across the organization. It’s a holistic approach to securing data from end to end.
Data security posture management (DSPM) is a specific tool that aids in the discovery and categorization of data. It is the foundation of data security because without discovery and categorization, you are left with assumptions and just a small portion of your sensitive data being protected.
Data security management is the game plan and DSPM is the scoreboard. But you need both to stay on top of your data security game.
The Final Word
Data security management doesn’t have an “off” switch. Threats are constantly poking around, cloud environments are shifting like sand dunes (be careful not to wake those worms!), and compliance rules are multiplying every time you blink. But most breaches don’t require a mastermind hacker in a hoodie, it’s usually because someone forgot to lock the digital front door. Or back door. Or fifteen side doors that no one remembered were there.
The key to staying ahead is knowing where your sensitive data is hanging out. Keep a close eye on who’s snooping around. And set up systems that yell at you (politely) when something’s off.
Because when it comes to data security, it’s not the most high-tech company that wins, it’s the one that remembers to do the obvious stuff. Consistently. With a little help from AI, and maybe a bit less caffeine-fueled panic.
So, while data security management might never be as easy as clicking “Accept” on that user agreement, with the right tools and best practices, you’ll be much better equipped to stay ahead of the curve.
