In today’s world, there is no organization or company that doesn’t have valuable data that needs to be secured. This data can be in the form of customers’ or clients’ personal information, transaction receipts, financial details, or more sensitive type of data.
In order to protect this data, there is a strong need for data classification, which is often considered the first tier in protecting the individual or collective information to reduce the risk of data breaches.
By knowing everything about data classification, you can develop professional workflows and processes that can be used in any industry to protect data. In this article, we will discuss:
- Data Classification Definition
- Why is Data Classification Important?
- When is Data Classification Required?
- Examples of Data Classification Tools
This is a part of our comprehensive data classification guide.
Data Classification Definition
Data classification refers to the method of assigning a category to data, depending on how sensitive it is. It is necessary for determining the type of security controls that need to be implemented for particular data based on its classification.
If you are a data classification or data management professional, you might work as a data scientist or manager in order to handle such operations.
An example of work that a data classification professional does is reviewing all the files and digital transactions for an organization, classifying all the data into categories, and designing and implementing parameters in order to safeguard each classification.
Data classification is integral for several industries, and it applies to different organizations and roles as well. To determine how data classification can be applied to your company, you need to consider several factors, which include the following:
- The nature and type of information collected from customers, clients, vendors, or other business entities
- The information or data created by your company, such as files, spreadsheets, receipts, customer profiles, etc.
- The security or sensitivity level of the data
- The people that need to access your data
- The frequency of data access
- The digital records maintained by your company
- The duration for which each category is documented
Why is Data Classification Important?
Let’s face it. Without data security, businesses can’t thrive. This is why data classification is crucial, and also because it helps you organize data to keep it secure, thus avoiding the likelihood of data breaches, cyberattacks, and hacking attempts. It acts as a firewall for businesses, especially since they have started using digital platforms like email, cloud computing, online payment, and several others.
If your business data gets compromised or leaked, it might have a low, moderate, or high impact. Therefore, it is important to find out the level of risk, and also implement protocols and measures that can be used to protect the data, and data classification is used for this purpose.
Basically, data classification can be used to:
- Protect the integrity and confidentiality of the data
- Prevent personally-identifying information and business information from getting leaked
- Comply with data privacy regulations and laws
- Determine who gets data access, as well as the frequency and method
- Establish the duration of record-keeping, as well as the security measures needed to protect the records
- Maintain client trust
- Establish a culture of data security
- Preserve the company and brand reputation
- Save time and money by placing targeted controls on integral data
When is Data Classification Required?
As mentioned above, data classification is necessary for every organization, and it is required when you have a large amount of sensitive data in your organization, as well as an influx of valuable data over time. If you don’t implement data classification protocols at the right time, you might risk having your data exposed to cyberattacks and data breaches.
When data classification is required largely depends on the sensitivity of the data that you are trying to protect. For instance, if your company’s data includes low-sensitivity information like public websites content, press releases, marketing materials, and other data, you are at a lower risk of getting your data compromised.
On the other hand, if your company information contains medium-sensitivity data, i.e. supplier contracts, IT service management information, organizational correspondence, and other types of information, you will need to implement data classification protocols as soon as possible.
Lastly, if you have high-sensitivity data like credit card information, customer personal data, privileged information, social security numbers, and similar information, then it becomes highly crucial for you to classify the data and implement security protocols as soon as possible.
Examples of Data Classification Tools
There are various types of data classification tools that companies can use in order to keep their data security in check, and also prevent their valuable data from being compromised. Moreover, these tools can be divided according to the various types of data they are used on, namely unstructured data, structured/semi-structured data, and continuous data classification.
Unstructured Data
Unstructured data refers to data that has no predetermined data model or pattern. Therefore, you can also call it qualitative data or unorganized data. Moreover, it isn’t easily searchable through artificial intelligence or machine learning. In simpler terms, unstructured data is created by individuals, rather than systems.
Some examples of unstructured data include audio files, text, presentations, social media data, videos, mobile usage data, etc. It can also include source code, binary code, documents, and many others. Data classification tools make use of machine learning algorithms to classify data based on their sensitivity, risk, availability, duplicity, and usefulness. Since this type of data can’t be analyzed by machines, they require additional processing.
Structured or Semi-Structured Data
As compared to unstructured data, structured data can be processed and analyzed by humans, and it can also be indexed.
Some of the examples of structured data include spreadsheets and database objects. Moreover, performing data classification on structured data is much easier and less complex as compared to classifying unstructured data.
Continuous Data
Continuous data refers to information that is in fractional numbers. This may include the Android phone version, a person’s height, the length or width of an object, and similar types of data. Basically, it represents data that can be broken down into smaller levels. This also means that the continuous variable can take any value within the range.
Summary
This concludes our guide on data classification examples and how data classification tools help you protect all types of sensitive company and customer data. Data privacy is the need of the hour, especially due to the wide range of data breaches occurring in the past. This is why organizations should protect the integrity and availability of their data.
Data Classification with Satori
Satori provides a different approach to data classification. With Satori, data is continuously discovered and classified, instead of performing ad-hoc scans.
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