When most people think about data, they might imagine a mad dash of numbers swarming across the screen in a frenzy. Unfortunately, they don’t always think about what those ones and zeroes might really mean.
If you’re talking about protecting student data privacy, they mean a whole lot. But not all personal data is created equal – some are more sensitive than others. That’s why classifying data by risk is a pivotal part of data loss prevention. For example, consider the amount of data a single student is creating on a daily basis, compounded by every other student in each individual school. Your district is collecting the whole spectrum of sensitive data from test scores to addresses to social security numbers.
Data classification and data loss prevention (DLP) go hand-in-hand. To understand why you can’t effectively do the latter without the former, here’s a guide through the ins and outs of data classification.
Imagine you’re putting away your groceries. Some fruits and vegetables might need to be protected in the refrigerator, others might need to be frozen, and a few are safe and sound on the kitchen counter. You wouldn’t put all your groceries in one place, just like you wouldn’t classify all your data the same way.
Data classification is essentially the same procedure. TechTarget defines data classification as the process of separating and organizing personal data into categories based on their shared characteristics. While certain types of data are low-risk, others might contain more sensitive information that needs to be tightly secured.
Why is classification important to data protection? Simply put, it’s what helps you allocate your data security resources most effectively. Think about it: If you don’t know your data, where it resides, or what it contains, how will you know where to focus your attention? That’s the type of insight data loss prevention depends on to easily locate, monitor, and apply the best protection.
Data classification is all about sorting structured and unstructured data. But what’s the difference?
In short, structured data is quantitative. For your district, that likely means test scores, birth dates, Social Security numbers, credit card numbers, and other sensitive information that might be represented numerically. On the other hand, unstructured data is qualitative, such as personally identifiable information found in text and image content.
In either case, data discovery methods will locate the created data and classify it in three ways:
Bottom line: The greater the sensitivity, the bigger the risk to data security.
Data classification and data loss prevention efforts are no simple task for many school districts. What should be a fast, simple, and automated process is often made more complicated than it needs to be.
There’s likely a number of barriers that challenge your ability to classify student data effectively and efficiently.
Let’s take a look at some challenges with which you might be familiar:
All told, any one of these challenges could spell trouble for your district’s data security. If left unclassified and therefore unprotected, sensitive data could fall into the hands of unauthorized third parties or cybercriminals. At that point, there’s no telling where that information might go or how it’ll be used.
When you consider the importance of organized data – or the dangers of unorganized data – it becomes clear that improving data classification should be one of your district’s top priorities. After all, an investment in data classification is an investment in your district’s safety.
And the good news? There’s plenty of benefits that make your investment worthwhile:
By now, you might be wondering: How can I start improving data classification today? To answer that question and help you realize the intended benefits, here are a few best practices:
Protecting your school district’s data might begin with data classification, but it doesn’t end there. ManagedMethods understands that effective data loss prevention is all about securing the entire data lifecycle. Our cloud security solution automates 24/7 data protection to help your team keep sensitive data out of harm’s way.
Ready to learn more? Check out our webinar for more information about protecting data privacy in education technology or request a free trial today.