Everything You Need to Know About Data Classification

Data Classification has proved to be an important part of the data management process over the years in various enterprises. 

It categorizes data and effectively stores, protects, manages your data and makes it ready for monetization. So, let’s dive in.

Data Classification

What is Data Classification?

Classification of data is a diversified process involving various data classification methods and criteria for categorizing data within your database. 

It helps to classify data according to your business requirements and organizational goals and to make it more useful and profit-oriented for data monetization.

You already have a database of your business or organization. It contains a large amount of data that is raw. But, you know that raw data is extensive and bulky to handle. So, it is difficult for us to draw meaningful conclusions from them.

On the other hand, data which is classified becomes simple and understandable. Also, it is easy to draw meaningful conclusions from them.

Hence, the importance of data classification for the growth of enterprises is phenomenal.

Understanding Classification of Data with an example:

Let’s suppose;

ABC Bank has a wide database that contains product information, customer details, employee charts, credit card transactions, customer PINs etc.

ABC Bank has to make crucial decisions regarding their data management and Information Privacy. To manage and secure their data, they need to classify their data using various types of data classification. The Classification would include sorting their data into Restricted Data, Confidential, Internal and Public Data.

Based on sensitivity, the bank would keep the customers’ credit card numbers in restricted access, and Contracts with suppliers would be kept Confidential.

Further, they have their Internal Data, including the Organizational Chart that is concerned with the Internal Corporate only. Data that contains customers’ details or banking offers are disclosed to all. So, they term this as their Public Data.

So, a well-defined Classification helps ABC Bank in deciding which Data in their vast database needs vital care and which needs ease. Also, data storage and privacy decisions of ABC Bank depends on this Classification.

It is thus evident that classified Data is the most useful and profitable for a business unit or organization.       

Why do you classify data? 

What are the reasons for classifying your data? You may classify Data for several reasons including ease of access, complying with regulations and in meeting other goals.

In other cases, the classification of data is a regulatory requirement because of the following reasons:

1) Easy identification of data:

With Classification, it becomes convenient for you to know what data you have and where it is located. This further helps you to retain and store your data easily.

2) Better planning of campaigns:

With classification, you can get clear insights on what data will work for you or which audiences work better. As a result, this can help you in scaling those campaigns and removing the non-working categories and campaigns from your marketing strategy.

So, you can invest money on the working categories and not on futile ones. Thus, classified data helps you to plan your campaigns and scale them in a better and feasible way.

3) Data Monetization and revenue generation:

With classified data, you can categorize your data and recognize the opportunity that your data contains. This way, you can take your data to the data markets and commercialize it for revenues.

Data Monetization is how you add insights to your data and share it in the marketplace to monetize it. Classified data provides a proper managed database of your app data as well, and this is how your apps can make money more effectively .

Thus, the classification of data helps in adding attributes to your data and use it to commercialize your new or existing businesses.

4) Security of data:

When you classify your data using data classification methods, it becomes effortless for you to secure your data by implementing a strategic security policy which goes hand in hand with your Regulatory Compliance

5) Protection of Data:

Classification helps to decide the categories of data. So, when you know which data is public, confidential and private, it becomes easy to discover which data you need to secure and which you need not. Thus, it helps in safety and compliances.

6) Prevent insider and outsider threats:

Data Categorization helps in drafting safe privacy policies, and so you can prevent the insider threats that stem from your employees’ weaknesses. 

Also, your data contains some files and documents that make their way outside the company. And, your third parties might be keen to see those data which they ethically shouldn’t. As a result, Classification of data helps to prevent unauthorized third parties from doing so and prevents outsider threats.

So, Data categorization or Classification is a useful tactic that facilitates proper data storage, security and helps data monetization effectively.

How do you classify Data?

So, what are the types of data classification?

Primarily there are two ways to classify data. You can either do it in an automated manner or manually.

An automated process can help you scale the procedure and operations quickly, whereas a manual process gives a direct touch to your data. 

There are three different types of types of data classification that drives information privacy and optimization decisions.

To start with;

1) Content-based Classification:

With Content-based classification, you can go through the files and documents in your database and check for the sensitive data. This information classification strategy uses fingerprinting and regular expression to review data.

It can help you to figure out what all does your data contain. Further, you can examine the files from the contents of your vast database. As a result, you can simplify your data using this strategy.

2) Context-based Classification:

Context-based classification is about answering basic data-related questions going on in your minds. For example; how are you using your data, who is the concerned person or persons connected with your data, where do you plan to move the data, i.e., to create, edit, copy or delete. Also, context-based refers to when are you going to access your data.

The difference between these two types of data classification is that the content-based classification talks about what all your database contains, while the context-based classification looks at the flow of your data.

3) User-based Classification:

User-based classification gives a personal touch to your data. It depends upon the knowledge of the user who is handling your data. It is about how the user who is accessing your data would edit, review and circulate the data.

In this way, Information Classification adds value to your data and thereby helps you to comply with your privacy policies and promote secured monetization.

You should leverage both these types strategically and employ them together to get the best policy for you. Categorization of data is mainly done on the basis of how sensitive your data is.

Implementing effective Classification of data: Strategy and Steps

Classification of data is the foundation of all the measures that you could take to make profits for your organization and ensure the security of your data. Your organization could fail to derive the outcomes that you want if you go wrong with the data categorization strategies.

You may classify your audience data strategically using various bases of data sensitivity and adopt a well-defined classification process. Let’s discuss in detail.

High sensitivity:

Your highly sensitive data information includes information that you can track personally. This Data contains employee records, medical records, financial account details, intellectual property, system user IDs and passwords.

You can also term your highly sensitive information as your confidential data or restricted data. If this data is somehow disclosed, it could be financially or legally risky for you and could expose your enterprises to severe damage, loss or legal consequences.

However, sometimes restricted and confidential data is separately classified, but you can term them in one group too owing to their highly sensitive nature.

Medium sensitivity:

Medium sensitive data is the Data, which is sensitive but is not highly-sensitive. It is the internal or company data for your company use only. 

This includes your internal emails and non-confidential business files used in daily operations.

Any unauthorized access to this data could be embarrassing; however, it wouldn’t be dangerous or tragic to your enterprise.

Low sensitivity:

Low sensitivity data is the public data or unrestricted information that your organization wants to make generally known to others. This includes your press releases, general sales and marketing material, and advertising.

Data Classification Categories

What should be your Steps to classify data ?

You should align a strategic well-defined classification process according to your own business needs. As you develop your data protection strategy, you can tailor with the classification process to meet your enterprise’s unique needs. 

Step 1. Establish an information classification policy.

You must define your classification policy according to the objectives you need to achieve. Go ahead and communicate the process to all the employees who deal with sensitive data. Simply, keep this policy short and straightforward and include the following essential aspects in it:

Firstly, determine the objectives as to why the classification has been put into place and what are the goals that the company expects to achieve from the process.

Secondly, you should decide the workflows, i.e. how you will organize the data classification process and how it will impact the employees who are dealing with sensitive data.

Thirdly, decide the Information classification scheme which talks about the classes into which you will classify the data.

The fourth important aspect of your policy is Data ownership. In this, you deal with your roles and responsibilities as to how you should classify sensitive data and grant access to it.

Fifthly, handle instructions properly, i.e. decide and implement a security standard that specifies proper handling practices for each data category and data classification types based on how sensitive that data is.

Step 2. Discover your sensitive data.

Once you establish the policy, you can move forward with the classification process to discover your sensitive data. Discovering your Data means to find out which data from your vast database needs more care and which needs ease in handling. 

Step 3. Apply classification labels to your data.

Optionally, it is up to you if you wish to give labels or names to each sensitive data of yours. You can do labelling manually or in an automated manner.

Because when you label your data, you can bring in more clarity to your process. As a result, this will smoothen the path of information classification and improve it for you.

Step 4. Use your results to improve data security and compliance.

Once you know what the sensitive data in your database is and where it is located, you can go ahead to review your security policies. Check the procedures to judge whether these policies and the data classifying strategy protects all your data. As a result, you can prioritize your efforts, control the costs involved and improve your data management processes.

Step 5. Repeat.

Your data is dynamic. It keeps on moving from one location to another, as you create, copy, move and delete files every day.  If you carry out the process correctly, you will be able to protect all your sensitive data, and thus, the classification of data or information classification is an ongoing process in the organization.

The most successful processes employ a polished data classification strategy, follow-up processes and frameworks to keep your sensitive data where it belongs.

Data classification methods and techniques help you to classify your raw data into useful data which plays a vital role in the storage, safety, security and compliance of your enterprise or organization.

Your success depends to a great extent on the Data classification methods and data classification types.

What elements should you look for in your Data Classification Tool?

Once you create a classification scheme, you should address the security standards. It is important to know what to consider when you are looking for the right information classification tool. There are certain basic requirements to look for. They are:

  • Data Classification tools should be functional in nature, i.e. the classifier and the interface you are using should be useful enough to facilitate efficient Classification.
  • Data Classification Tools should include those tools that are easy to use and goes at ease with your data classification strategy. This helps your organization in understanding the entire classifying procedure with convenience.

As technology is advancing ahead, efficient Data Classifying tools are the need…

  • Data Classification Tools should ensure that no matter where you move, copy or send your data files and documents to, that concerned file and docs remain classified at the changed storage location too.
  • One important requirement you need to take care when choosing the classification methods and tools is an easy integration. The tools should integrate with your current DLP system with ease.
  • The amount of Data you exchange within your business unit or organization, as well as external partners, is high. With data classifier tools, you can easily manage and retain data and store the necessary Data properly and safely.
  • You will keep facing issues regarding data management. So, Data Classification tools should patch the possible gaps in your data security.
  • Inevitably, this would burden in controlling information and data content. As a result, the safety and security of your data becomes a major concern. So, Data classification tool is vital for your enterprise. 

 What is the importance of ‘Classifying your Data’?

  There’s a great importance of data classification for your organization. 

  •  It allows your business or organization to apply appropriate controls based on category data. You can work accordingly, and you don’t necessarily need to have the same kinds of controls for all types of data.
  •  Classifying your data saves you time and money. Because classification focuses on what is important and what isn’t, you don’t waste your time putting unnecessary controls in place.
  •  With Data Classification methods, you can sort which data is sensitive and which is not. As a result, you can minimize the risks of sensitive data and enhance the effectiveness of DLP.
  •  One major importance of data classification is that it protects your information and provides it security. In this way, it safeguards any information breaches that could have happened somehow. 

Is Data Classification a win-win for you?

In conclusion, your data classifying strategy is the cornerstone of successful and secure use of data in your organization. Right from the time you create data until its destruction, you need to take care of the Data you possess. So by classifying, you can adequately protect your data, store it properly and manage it well.

When you employ the right information classification strategies for your organization, you will be able to comply with the legal and regulatory framework of your enterprises.

It would help you increase your data awareness by understanding better about which data is sensitive.

Consequently, you can promote better decision-making and maximize your opportunities for Data Monetization. Thus, Data classification is a game-changer for your business and organizational efficiency. So, always keep your business needs in mind and draft a win-win strategy to move ahead.

So, how have you set your enterprises up for success with data classification?

I would love to hear about your experience in the comments.

Sonali

Sonali is a technical content writer who loves to blend her creativity with rational ideas of business and technology. She intends to keep it up with the digital trends and accommodate within herself the upcoming trades. She writes expert resource materials related to the Martech and adtech world. Previously worked as a banker, she has been a student of Economics and Human Resources. An ardent believer of Universe and optimism, she writes poetry and quotes to satiate her soul. Always keen about nature, travelling, music and photography.

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