More than 2.5 quintillion bytes of data are being generated daily, and this number is only growing. This vast pool of data plays a vital role in any organization’s success. However, how do businesses manage to get valuable insights from this large dataset? The answer lies in data classification. This innovative method not only classifies data according to its sensitivity but also helps businesses retrieve valuable insights to gain a competitive edge.
As per Extrapolate, the data classification market is projected to garner $1,857.7 million in revenue by 2030, expanding at a CAGR (compound annual growth rate) of 25.8% over 2022-2030. In this blog, we will explore the importance, types of classification of data and learning, and the best practices for making an effective policy for them.
What is Data Classification?
Data classification is the process of categorizing files, databases, and other data into logical groupings. This classification is made based on the data’s content, importance, and value to the organization. Data categorization helps organize data for the responsible use and protection of imports. This simplifies the process of locating and retrieving vital information and reduces duplication and storage costs.
Classification of data is important for data security and compliance, particularly for companies that store large amounts of predetermined data. It helps businesses comply with regulations, manage risks, and maintain data integrity.
What are the Four Types of Data Classification?
Data classification categories are defined based on the sensitivity of information or content. The four main categories of data are as follows:
- Public data: This type of data is freely available to the public. It can be freely used, reused, and redistributed without restriction. The best examples are job descriptions and press releases.
- Internal-only data: This type of data is strictly accessible to internal company employees who are granted access.
- Confidential data: This information can only be accessed by a limited number of individuals with proper authorization. This offers controlled access to data and uses identity and access management (IAM) tools to control access to confidential data.
- Restricted data: This is the classification used for the most sensitive information. This data has strictly controlled access that prevents its unauthorized use, and it needs to be encrypted for additional protection.
Data Classification Best Practices for Creating Policies
An effective data classification policy plays a vital role in business functions by meeting compliance audits, conducting mergers, or protecting company rights while saving money. Below are some best practices for creating a promising data classification policy.
- Conduct regulatory analysis regularly and classify data based on business standards and privacy requirements.
- Use advanced tools and software that help analyze and separate data to simplify classification according to guidelines.
- Understand your data profile to determine collection, storage, accuracy confirmation, responsibility, and data management.
- Set plans and measurable goals to align with the company’s principles and objectives.
- Make policy simple with minimum classification categories.
- Specify work ownership to divide responsibilities and ensure accountability.
- Review the policy each year to stay up-to-date with the company’s internal and external changes.
Top 3 Free Data Classification Tools
Take a look at the free software listed below to classify data.
1. Ground Labs: Enterprise Recon PRO
Ground Labs offers Enterprise Recon PRO – a globally recognized solution for data discovery with metadata tagging and PII data classification capabilities. It also offers on-demand data discovery and data management capabilities.
2. Imperva Classifier
The Imperva Classifier is a tool used for the classification of data. It includes over 250 search rules for leading enterprise databases. It can be downloaded for free by completing a form with an accurate email address.
3. ManageEngine DataSecurity Plus
ManageEngine offers a DataSecurity Plus free trial for 30 days, allowing users to download and use the tool for data classification and labeling. This data classification software also offers cloud protection features for monitoring web traffic and generating reports on upload requests.
China’s Data Classification and Security Rules in 2024
In April 2024, The National Financial Regulatory Administration released draft measures for data security management of banking and insurance institutions, aligning with China’s Data Security Law, Cybersecurity Law, and Personal Information Protection Law. These regulations mandate the data security control structures and accountability systems in the financial institution sector, with specific roles defined for each department. This specifies the following rules:
- Data classification is based on the importance and sensitivity of the data, and financial institutions must establish a data classification and protection system.
- Financial institutions are prohibited from outsourcing responsibilities for IT management and data security and must devise plans based on the “necessary authorization for business” principle and implement effective technical protective measures to ensure data security.
- data security responsibilities and obligations in contracts should be clearly defined for all parties involved.
Additionally, in May 2024, China’s State Administration of Market Regulation (SAMR) and the Standardization Administration of China (SAC) released a new set of technical standards for data classification. Its technical standards, titled Data Security Technology, set rules for data classification and grading. It also outlines rules for classifying three types of data and provides a general guide for companies and government ministries to comply with China’s personal information and data protection regulations. The standards will be implemented on October 1, 2024, for core and important types of data protection requirements.
Bottom Line
Data classification is vital to organizing, securing, and utilizing data effectively. By categorizing data based on its sensitivity, relevance, and purpose, businesses can streamline their operations, enhance data security, and ensure compliance with regulations. This process enables better decision-making, efficient information retrieval, and protection of sensitive information. As technology continues to advance, the importance of data classification will only grow, making it a pivotal tool for businesses and individuals.
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