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You can’t protect what you don’t know. Yet, when you consider that 80-90% of businesses’ data is unstructured—like emails, documents, and web and mobile data—business owners are leaving a lot up to chance.
It’s not that unstructured data is bad. In fact, unstructured data, such as invoices and product reviews, can give businesses valuable insights and help build closer and more profitable relationships with customers. Rather, it’s the systems used to store and protect this data that leave businesses vulnerable. At best, poorly managed data gives your team a headache when they need that crucial piece of information for a product. At worst, mismanaged data leaves you open to cybersecurity attacks that put your reputation and ability to do business at risk—just ask the 47% of companies that were impacted by a cybersecurity attack in 2021.
The need for proactive data management is clear, but how do you get started? After all, if keeping track of unstructured data was as simple as entering it into a database like it is for structured data, you’d be doing it already. At DryvIQ, we believe that the first step to securing your data is through sensitive data discovery. This process analyzes, classifies, labels, and catalogs unstructured data, so it is easy to automatically sort and interpret.
To help you start on your journey to unstructured data that is organized and protected, this article will answer questions such as:
- What is data discovery and why is it important?
- How do you do data discovery?
- What is a discovery tool for sensitive data?
- Where can you find the best data discovery and classification tools?
As we go through the reasons why data discovery is important and how it works, take note of your current data management practices. These questions can be a good starting point:
- What types of data do we keep that don’t fit easily into databases?
- Do we have unstructured data that contains sensitive information, such as medical records or plans for new products?
- Do our team members ever have difficulty tracking down necessary information?
Let’s dive in!
The best way to keep track of all of your data that needs to be protected is with a data discovery platform. In short, data discovery platforms use artificial intelligence to scan indicators such as file properties, applied metadata, keywords and patterns. This allows unstructured data that has complex identifiers, like email threads, to be sorted into databases. Organization helps to overcome many of the vulnerabilities caused by how sensitive data is often stored. In other words, once you know where your data is, it’s a lot easier to keep it safe.
We’ll see exactly how data discovery works in more detail soon, but first, let’s look at current data storage methods and where they fall short.
How Is Sensitive Data Stored?
Structured sensitive data is often stored in secure databases; however, the issue is unstructured data that is accessible from many devices that can make and keep their own copies of that data. To see just how chaotic—and insecure—unstructured data management can become, let’s take a look at an example:
Fred owns a bakery, and he is very proud of his secret cupcake recipe that his customers can’t get enough of. The thorn in Fred’s side, however, is that he can’t run a business on delicious baked goods alone. He needs data, and lots of it. Here’s just a glimpse of the information that Fred’s business receives and stores on a daily basis:
- Catering invoices
- Debit and credit card information
- Customer contact information for his loyalty program
- New (secret) recipe ideas
- Utility bills
- Supply invoices
- Employee information
- Employee communications, including text and email conversations
- Graphics for social media posts
- Marketing performance metrics
- Financial records
Some of this data is structured, some is unstructured, and these data points have varying levels of sensitivity. Data that has low sensitivity can be safely shown to the public—think billboards, for example. Highly sensitive data can only be viewed by a select group of people, otherwise the business could be compromised—such as proprietary software code or that secret recipe. Let’s break it down further by structure then sensitivity level:
- Customer contact information. Medium sensitivity.
- Financial records. High sensitivity.
- Debit and credit card information. High sensitivity.
- Employee information. High sensitivity.
- Financial records. High sensitivity.
- Marketing performance metrics. Medium sensitivity.
- Graphics for social media posts. Low sensitivity.
- Secret recipes. High sensitivity.
- Catering invoices. High sensitivity.
- Utility bills. Medium sensitivity.
- Supply invoices. Medium sensitivity.
- Employee communications. Medium sensitivity.
Fred is able to stay on top of his structured data fairly well and keeps it organized in secure spreadsheet programs. However, he is less organized when it comes to his business’s unstructured data. Why does Fred have so much trouble keeping his unstructured data organized? Because he doesn’t see just how much of his data is unstructured and vulnerable. After his social media intern creates a clever graphic to post to social media, Fred puts it in his Social Media folder, but he changes his file naming conventions every time. He keeps his secret recipes in a password protected folder. Yet, when he emails them to his head baker, he downloads and saves them in a location he can never seem to find again, so he has to download multiple copies.
How does this impact Fred, his employees, and his business? To start, Fred doesn’t realize that when he shares sensitive information like passwords through email, it heightens the risk of a data breach. His inconsistent file storing methods also make it difficult to use past data to inform current decisions. He often asks questions like: “Where’s our new Facebook ad” and “Did Joey’s birthday party pay for catering yet?” His employees don’t know where to find that information quickly, either, which causes frustration at the bakery. It also causes embarrassment for Fred when he calls a catering customer to request payment after they’ve already paid him.
While this example shows how easy it is for a small business to lose track of important and sensitive unstructured data, it is just as easy for enterprise level companies to find themselves in this situation. And, if unstructured data can pose such a high risk to a small business, imagine the impact it could have on a multi-national company with thousands of employees. Take Salesforce, for example. In 2017, a member of Salesforce’s board had their email hacked, which exposed acquisition targets that were normally stored securely—except when they were being communicated over email. No matter how big or small your business is, unstructured data leaves you vulnerable to inefficiencies and security risks. So what can you do to get organized so you can be protected? We’ll cover that next.
Sensitive unstructured data can be stored in a database after you give it some organizational structure, which can be done quickly and to scale with an A.I. powered data discovery solution. First, you need to understand how much data you are dealing with and where it is all located. Then you can categorize your data, store it in appropriate locations, and implement security measures.
What Is Sensitive Data Discovery?
Sensitive data discovery is the process of identifying points of data, measuring their risk level, and either clearing out those data points or properly securing them. Sensitive data discovery comes with numerous benefits, which include:
- Staying compliant with regulatory bodies, such as the Health Insurance Portability and Accountability Act (HIPAA)
- Protecting your reputation, which could be severely damaged by a data breach
- Reducing the amount of sensitive data you need to keep stored
- Saving on storage costs
What Are Data Discovery Tools?
Sensitive data discovery tools make it easy for businesses to see where their data is, categorize and organize it, and then analyze that data for valuable insights. An effective data discovery platform will include the following four tools:
Advanced Pattern Matching
Data discovery tools can group points of data together based on patterns. Common examples include phone numbers, social security numbers, and government document IDs. Artificial intelligence can detect when data points share patterns, like the number of digits they contain. Some tools, like DryvIQ, can also use keyword proximity to make more advanced connections.
Document Type Classifier and Standardized Form Matcher
Text- and image-based documents can be very difficult to keep track of, but data discovery tools can identify categories such as resumes, contracts, court documents, HR files, financial reports, and so much more. This means that you no longer have to rely on file names to find important tax forms or design files.
PII Identification and Extraction
Most personal identifiable information falls under structured data, but what about phone numbers and addresses that are only present in documents? Using deep learning technology, data discovery platforms can extract personal information from documents while also categorizing those forms. For example, all forms with social security numbers could be marked as highly sensitive.
Hundreds of languages are spoken around the world, and business is conducted in each and every one of them. With language detection tools, you can group documents by shared languages. You’re not limited to spoken languages, either. Data discovery tools can even pick up on non-natural languages such as coding and machine generated files.
What Data Tools Can Be Used for Data Discovery?
A combination of the above tools should be used for a comprehensive data discovery plan, and many organizations would benefit specifically from PII data discovery tools and payment card industry (PCI) data discovery tools. Why are these two of the most common tools? Because every business needs customer data—both personal and payment information. While this data is necessary, storing it comes with risk. If customers find out that you allowed their data to be exposed, they’ll lose trust in your company and may even face hardships because of it, especially if their credit card information gets in the wrong hands.
Great data discovery tools tell you what your data is, where it’s located, who can access it, and if it is sensitive. DryvIQ answers these questions with data discovery that is accurate, scalable, advanced, and designed to turn your unstructured data from a liability into an asset—just like it should be.
With advanced pattern matching, document type classifier and standardized form matcher, PII identification and extraction, and language detection all wrapped into one data discovery tool, it’s never been easier to take control of your data. Whether your goal is to better meet compliance, take a proactive approach to cybersecurity, or clean up the data you store, DryvIQ is here to make it happen. To see how your business can benefit from data discovery tools, schedule a demo today!