Data Classification 101: Navigating Types, Objectives and More
Share this article
Data classification is a crucial process that empowers business owners and decision-makers to organize, use, and safeguard their information effectively. In this article, we will unpack what data classification entails, its primary objectives, and the different types that exist.
We’ll also provide insights into the methods, standards, and policies that underpin this practice.
Modern data problems require modern solutions - Try Atlan, the data catalog of choice for forward-looking data teams! 👉 Book your demo today
Understanding these elements is vital as they directly impact the security and efficiency of your business operations.
Join us as we navigate through the complexities of data classification, simplify its challenges, and explore the technologies that can streamline its implementation in your organization.
Table of contents
- What is data classification?
- 5 Key objectives of data classification
- 3 Types of data classification
- Methods of data classification
- Data classification standards and policies
- 7 Data classification challenges
- Data classification technologies
- Implementing data classification in organizations
- To summarize
- Related articles
What is data classification?
Data classification is the process of organizing data into categories that make it easy to find, use, and protect.
Think of a library with thousands of books. If the books were scattered everywhere, finding the one you need would be a nightmare. But libraries have sections and labels, making it simple to find a book.
Data classification does something similar for the information in a company. It tags and sorts data so you know what you have, where it is, and how important it is to your business.
5 Key objectives of data classification
When it comes to handling information in a business, it’s crucial to sort it based on its importance and sensitivity. This process is called data classification. The main goals of this practice are to protect your data, follow laws and rules, and make sure that only the right people have access to certain information. Key objectives are:
- Protecting sensitive information
- Complying with regulations
- Enhancing operational efficiency
- Managing access to data
- Reducing costs
Let’s break down these objectives to understand why they matter for your business.
1. Protecting sensitive information
The first and foremost goal of classifying data is to keep sensitive information safe. This could be anything from personal details about your customers to your company’s financial records.
By categorizing data, you ensure that highly sensitive information gets the highest level of protection, reducing the risk of it falling into the wrong hands.
2. Complying with regulations
Many industries have rules about how certain kinds of data should be handled. For example, if your business deals with health records, there are strict laws about how that information must be protected.
By classifying your data, you make sure that your business follows these rules, which can save you from hefty fines and legal issues.
3. Enhancing operational efficiency
By organizing your data, you help your team find the information they need quickly and easily. Think of it like a library system; if every book was just scattered around, it would be impossible to find what you’re looking for.
The same goes for your business data. When it’s sorted properly, your team can work more efficiently.
4. Managing access to data
Not everyone in your company needs access to all types of data. For example, your marketing team might not need to see the financial records. Classifying data helps you set up clear rules about who can see and use different types of information.
This way, employees only access the data they need for their work, which keeps things simpler and more secure.
5. Reducing costs
When you have a good handle on your data, you can also manage your storage costs better. Not all data is created equal; some need to be kept on hand and easy to access, while other data can be archived or even deleted.
By classifying your data, you ensure that you’re not spending money to store information that’s not valuable to your business.
Data classification is a critical step in managing your company’s information. It helps keep sensitive data safe, ensures you’re following the law, makes your team more efficient, controls who can access what information, and can even save you money. For these reasons, it’s a practice that every business owner and decision-maker should understand and implement.
3 Types of data classification
When we talk about data classification, we’re essentially sorting data into different buckets based on how sensitive it is. Think of it like organizing your clothes; you have casual wear for everyday use, business attire that’s a bit more private, and perhaps special occasion outfits that are only for certain eyes.
Similarly, data is organized so that everyone in your company knows how to handle it. There are three main levels we’ll discuss:
- Public data
- Confidential data
- Secret data
Let’s understand these classifications in detail.
1. Public data
Public data is like the clothes you wear to the grocery store. It’s information that anyone can see without any worry. This includes things like your business’s address, the hours you’re open, and the services you offer.
It’s the kind of data that you would put on a flyer or a public website. You want this information to be easy to find because it helps customers learn about your business.
2. Confidential data
Confidential data requires more caution. This is the kind of information that you wouldn’t want everyone to know, like a customer’s credit card details or an employee’s home address. Think of it as the business attire of data; it’s not for everyday viewing.
To make sure only the right people see this information, you might need a key, like a password or a security badge. It’s essential that only the employees who need this information to do their jobs can access it.
3. Secret data
Secret data is your top-level, special occasion information. This could be your secret recipes, new product designs, or big business plans for the future. It’s the kind of data that, if it fell into the wrong hands, could really hurt your business.
Access to this data is highly restricted and might require not just one, but several keys to access it, such as multiple passwords, security tokens, and maybe even a thumbprint or a retinal scan.
Each level of data is important and needs to be handled properly. By classifying data, everyone in your business can understand at a glance how to treat different types of information, helping to keep it safe and secure. Remember, good data management is not just about avoiding leaks or thefts; it’s about knowing how to treat your business’s information as the valuable asset it is.
Methods of data classification
When it comes to sorting and securing your company’s information, there are a few ways to go about it. Think of data classification as organizing your business files into different cabinets for easy access and protection. Let’s explore the main ways you can do this:
- Manual data classification
- Automated data classification
- Hybrid approaches
Let us understand these methods in brief.
1. Manual data classification
Manual classification is like sorting through your papers and deciding where they should go based on what they contain. It requires someone to look at each piece of information and decide how sensitive it is. If a document has personal details about customers, it might be marked as confidential.
This method gives a personal touch and can be very accurate since it relies on human judgment. However, it can take a lot of time, especially if your business has tons of data to go through. It’s also possible for mistakes to happen because, well, we’re all human.
2. Automated data classification
Automated classification uses software to scan through your data and organize it. It’s like having a super-smart assistant who can quickly file everything correctly without getting tired. This method is fast and can handle a lot of data at once.
The software can look for certain words or patterns that help it decide how sensitive the data is. For example, it can identify and protect any document that contains a credit card number. The downside? It might not catch everything since it follows a set of rules and doesn’t understand context as we do.
3. Hybrid approaches
A hybrid approach combines the best of both worlds. Here, you’d use software to sort through the bulk of your data, but you’d also have people check over the results or make decisions on the trickier cases.
It’s like having a machine do the heavy lifting while a skilled worker does the fine-tuning. This method can save time and reduce errors, making sure that your data is sorted accurately and efficiently.
How you classify your data will depend on the size of your business, the type of information you handle, and how much time and resources you have. Each method has its benefits, but the most important thing is that you do classify your data. It helps keep your business’s information safe and well-organized, which is key to operating smoothly and maintaining your customers’ trust.
Data classification standards and policies
When you’re running a business, it’s crucial to keep your information organized and safe. Think of data classification as sorting your data into different groups, much like how you might sort files into folders.
This helps you manage who can see and use your business’s information. Some data might be open for everyone, while other information is strictly for certain eyes only. To do this effectively, there are rules and best practices you should follow.
Overview of industry standards
Imagine you have a set of instructions that tell you the best way to sort and protect your data. These instructions are known as industry standards. One of the most recognized sets of instructions is called ISO/IEC 27001.
This standard gives you a plan to manage your data securely, covering everything from how to start, what to do, and how to check if you’re doing it right. It’s like a quality seal that tells others you take data safety seriously, which can be great for your business’s reputation.
Government and regulatory policies impacting data classification
Different places have different rules about how data should be handled. Governments create these rules to make sure personal and sensitive information is not misused or gets into the wrong hands.
For example, in the European Union, there’s a rule known as GDPR, which is all about protecting personal data. It’s important to know the rules that apply to your business because not following them can lead to big fines and harm your business’s trustworthiness.
Company-specific policies and best practices
Your company should have its own set of rules for how to handle data. These are policies you create that fit your business’s specific needs and comply with the broader rules we just talked about.
For example, you might decide that only senior managers can access customer financial information. You should write these rules down, train your team on them, and check regularly to make sure everyone’s following them. It’s also smart to look at what has worked well for other businesses and consider adopting similar practices.
Remember, sorting and protecting your data isn’t just about following rules; it’s about being responsible and earning trust. A solid approach to data classification helps you run your business smoothly and keeps your customers’ and employees’ information safe.
7 Data classification challenges
In the world of business, keeping your data in order is like organizing a library. It sounds straightforward until you face the real-life challenges. Let’s talk about some of the common hurdles you might encounter when classifying your data. They are:
- Handling unstructured data
- Balancing security with access
- Keeping up with laws and regulations
- The human factor
- Technology can be a double-edged sword
- Consistency is key
- Evolving business needs
Let us understand these challenges in detail.
1. Handling unstructured data
Think about all the emails, documents, and other files your business creates daily. They don’t come in a neat package, making them hard to sort through. This is what we call ‘unstructured data’, and it’s a bit like trying to organize a pile of papers without any labels.
It’s tricky because this kind of data doesn’t follow a set format, and it’s tough to categorize using simple rules.
2. Balancing security with access
You want to keep your data safe, but you also need the right people to access it when necessary. It’s a delicate balance. Locking away data too tightly might hinder your team’s ability to do their jobs, but being too lax could lead to security risks.
It’s like keeping a door locked but making sure those who need to can still get the key.
3. Keeping up with laws and regulations
Laws about data privacy are always changing, and they can vary from place to place. Staying on top of these can be as complex as trying to keep up with the latest fashion trends — as soon as you think you’ve got it, it changes again.
You have to make sure that your data classification aligns with these laws to avoid hefty fines and protect your customers’ privacy.
4. The human factor
Even the best plans can go awry if the people involved don’t follow through. Training your team to understand and correctly apply data classification can be as challenging as teaching someone a new language. And just like language learning, it requires consistent practice and reinforcement.
5. Technology can be a double-edged sword
On one hand, technology offers tools that can sort and classify data almost like magic. On the other hand, these tools can be costly, complex, and sometimes they might not work with the other systems you already have in place.
It’s a bit like finding a piece of puzzle that doesn’t fit into your puzzle board.
6. Consistency is key
Imagine if every department in your company sorted their files differently. It would be chaos, right?
Consistency in data classification across all areas of your business is crucial, but achieving it is not always easy. It requires clear rules and regular checks to make sure everyone is on the same page.
7. Evolving business needs
Your business is alive, and like anything alive, it grows and changes. The ways you classify data today might not fit tomorrow’s needs. It’s important to regularly revisit and update your data classification practices, just like you would check on the vital signs of a growing plant.
Addressing these challenges may not be easy, but it’s vital for the health and efficiency of your business. Think of data classification as the foundation of a building. Get it right, and you’ll have a stable base for your business operations to grow and thrive.
Data classification technologies
Data classification technologies come in different shapes and sizes, but they all serve the same purpose: to help you sort your data into different buckets based on how sensitive they are. Imagine you have a vault, a locked drawer, and an open shelf.
You wouldn’t put your most valuable possessions on the open shelf for everyone to see. Similarly, these technologies help you put your most sensitive data in the vault, less sensitive data in the locked drawer, and the general information on the open shelf.
Manual versus automatic
You can classify data manually or automatically. Manual classification is like organizing your bookshelf by hand. It’s thorough, but it takes a lot of time and effort.
Automatic classification, on the other hand, is like having a smart robot that knows where each book should go. It’s faster and can work around the clock, but it needs to be set up correctly to make sure it doesn’t misplace a book.
The rise of smart solutions
The latest data classification technologies are getting smarter. They use patterns and rules to understand what data looks like and where it should go. Some even learn as they go, getting better over time at sorting your data.
This is a game-changer because it means you can trust these systems to handle more and more of your data organization, freeing you up to focus on your business.
Keeping up with change
One of the best things about modern data classification technologies is that they can adapt. As your business grows and changes, these tools can adjust to new types of data and new classification rules. This flexibility is key in a world where the only constant is change.
Integration into your business
Implementing these technologies into your business doesn’t have to be a headache. Many options are designed to fit seamlessly into your existing systems. They work quietly in the background, sorting and securing your data without disrupting your day-to-day operations.
The bottom line
Investing in data classification technologies is like investing in a good security system for your home. It’s about making sure that your most valuable assets are well-protected and that you can sleep a little easier at night knowing they’re safe. For a business owner or decision-maker, it’s not just a smart choice; it’s an essential one.
Data classification technologies are not just another piece of IT jargon; they are the backbone of effective data management. By using these tools, you can ensure that your business’s data is sorted, accessible, and, most importantly, secure.
Implementing data classification in organizations
When you’re running a business, you’ve got a lot of information flowing through your company. Some of this information might be things you’re okay with sharing, like your business hours or the services you offer.
But some information is sensitive and should be kept under wraps, like customer details or your secret sauce recipe. This is where data classification comes in. It’s like deciding which documents go into a locked cabinet and which can be left on the desk for anyone to see.
Steps to develop a data classification policy
Developing a data classification policy is a crucial step for any organization that handles sensitive or confidential information. This policy helps in categorizing data based on its sensitivity and lays out guidelines for its protection and handling. Here are the steps to develop a comprehensive data classification policy:
- Define the purpose and scope
- Identify stakeholders
- Data inventory and categorization
- Data classification criteria
- Data handling guidelines
- Access control and authentication
- Data labeling and marking
- Training and awareness
- Incident response plan
- Regular audits and reviews
- Legal and compliance considerations
- Documentation and communication
- Feedback mechanism
- Enforcement and consequences
- Periodic updates
Let’s look at each of the steps in detail:
1. Define the purpose and scope
Start by clearly defining the purpose of the data classification policy. Determine the scope of the policy by specifying the types of data it will cover. This may include customer data, financial records, intellectual property, or any other sensitive information relevant to your organization.
2. Identify stakeholders
Identify the key stakeholders involved in data management and security within your organization. This may include IT personnel, legal experts, data owners, and senior management. Involve them in the policy development process to ensure a well-rounded perspective.
3. Data inventory and categorization
Conduct a thorough inventory of all data assets in your organization. Categorize data into different classes or levels based on its sensitivity. Common classifications include public, internal, confidential, and highly confidential.
4. Data classification criteria
Develop clear criteria for each data classification level. For example, confidential data might be defined as information that, if compromised, could have a severe impact on the organization, while public data is information that can be freely shared.
5. Data handling guidelines
Specify how each classification level should be handled, stored, transmitted, and disposed of. Include encryption requirements, access controls, and retention policies. Ensure that these guidelines align with legal and regulatory requirements.
6. Access control and authentication
Define who has access to each classification level and how access is granted and revoked. Implement authentication mechanisms like strong passwords, multi-factor authentication, and role-based access control to ensure data security.
7. Data labeling and marking
Establish a consistent labeling and marking system for data assets. This helps employees easily identify the classification level of data they are working with. Labels can be physical (e.g., on paper documents) or digital (e.g., in file headers).
8. Training and awareness
Develop a training program to educate employees about the data classification policy. Make sure all staff members understand their responsibilities in handling data according to its classification level. Regularly update training materials to reflect changes in the policy.
9. Incident response plan
Create an incident response plan that outlines the steps to be taken in case of a data breach or unauthorized access to sensitive information. Define roles and responsibilities for incident response team members.
10. Regular audits and reviews
Establish a schedule for regular audits and reviews of the data classification policy and its implementation. This ensures that the policy remains up-to-date and effective in protecting sensitive information.
11. Legal and compliance considerations
Ensure that the data classification policy aligns with relevant laws and regulations, such as GDPR, HIPAA, or industry-specific standards. Involve legal experts to review and validate the policy from a compliance standpoint.
12. Documentation and communication
Document the data classification policy in a clear and easily accessible format. Communicate the policy to all employees and regularly remind them of their obligations regarding data classification and security.
13. Feedback mechanism
Establish a feedback mechanism to allow employees to report concerns or suggest improvements to the policy. Encourage a culture of continuous improvement in data security.
14. Enforcement and consequences
Clearly outline the consequences of violating the data classification policy. This may include disciplinary actions or legal consequences. Ensure that enforcement is consistent and fair.
15. Periodic updates
Recognize that data classification needs may evolve over time. Periodically review and update the policy to adapt to changing business needs, technology advancements, and emerging threats.
By following these steps, an organization can develop a robust data classification policy that not only protects sensitive information but also fosters a culture of data security and compliance throughout the organization. Regular monitoring and adaptation are key to ensuring the policy remains effective in the face of evolving data-related challenges.
Training and awareness for employees
Your data classification policy won’t do much good if your team doesn’t know about it or understand it. Training is crucial. The following steps can help you better train the employees and generate awareness among them:
- Regular training sessions
- Resources and materials
- Create a culture of security
Let’s look at them below:
- Regular training sessions
Hold workshops or sessions that teach your team about the different types of data, the categories you’ve set, and the importance of following these rules.
- Resources and materials
Give your employees cheat sheets, guides, or posters that they can refer to when they’re not sure about something.
- Create a culture of security
Encourage your employees to take data security seriously. Make it part of your business’s culture.
Monitoring and enforcing compliance
Once your policy is in place and your team is trained, you need to make sure everyone’s following the rules. Follow the below aspects to ensure for monitoring and ensuring compliance:
- Regular checks
- Technology helps
- Act on issues
- Update your policy
Let’s look at them below:
- Regular checks
Have regular reviews where you check if the information is being handled correctly. This could be a quick look at recent documents or a more formal audit.
- Technology helps
Use software that can help you keep an eye on your data. This software can alert you if someone’s not following the policy.
- Act on issues
If you find that someone isn’t following the policy, act on it. This could mean more training or even disciplinary action if needed.
- Update your policy
Keep in mind that your business will change and grow, and so will the types of data you deal with. Your policy should be a living document that gets updated regularly.
Think of data classification as a way to make sure your business’s information is only seen by the right eyes. It’s about keeping things orderly and safe, which is something any business owner or decision-maker should care about. By setting clear rules, training your team, and making sure those rules are followed, you can protect your business and your customers.
Data classification is a crucial step for businesses to protect and efficiently manage information. It organizes data based on sensitivity, ensuring compliance and security. While it presents challenges, including adherence to complex standards and handling diverse data types, the right technology can streamline and simplify the process.
For business leaders, embracing data classification is not optional but essential. It’s a continuous commitment to data integrity and a proactive stance on information security.
Implementing and maintaining a data classification system secures a company’s most valuable assets and instills a culture of awareness, safeguarding the business’s future in an increasingly data-driven world.
- Data Classification and Tagging: How to Marie Kondo Your Data Catalog and Spark Joy
- Data Governance vs Data Classification: 5 Key Differences
- Data Catalog and Data Governance: How Do They Complement?
- Agile Data Governance Model: Concept, Importance, Components, and Best Practices
- Active Data Governance: What It Is and How to Get Started
Share this article