How do you classify and label data for easy retrieval?

It involves establishing a system for sorting data based on a unique identifier which could be the same subject matter or chronology. Classification and labelling solves the challenges associated with users having difficulty retrieving documents.

Data classification levels by themselves are simply labels (or tags) that indicate the value or sensitivity of the content. To protect that content, data classification frameworks define the controls that should be in place for each of your data classification levels.

Data is classified according to its sensitivity level—high, medium, or low. High sensitivity data—if compromised or destroyed in an unauthorized transaction, would have a catastrophic impact on the organization or individuals. For example, financial records, intellectual property, authentication data.

To do this, use descriptive and meaningful names that reflect the content and purpose of the data. For example, "Monthly Sales Report - June 2021" or "Customer Feedback Survey - Q2 2021". Moreover, stick to consistent and standardized formats and conventions for data names, such as capitalization, punctuation, spelling, or abbreviations. Dates and versions can help track changes and updates of the data, such as "Draft v1" or "Final v2".

It’s worth noting that data labeling standards (and adhering to them!) make it easier to find things in shared spaces not only for routine work, but also in the case of an audit or for legal matters. Or what if someone leaves the company and someone else needs to find something? However, it’s often underestimated how much value following data labeling and storage standards has on an individual basis as well. Have you ever thought you lost an important document only to find it in some other folder? Accidentally deleted something out of your downloads folder because you left it there too long? Can’t remember which “FINAL FINAL RESUME DRAFT FINAL” is really your final draft of your resume?

Labeling data and also the platform in which the data is stored must be consistent and streamlined across individual departments. The data storage and labeling should also be structured and written within your organizations operating procedures. I would also highly suggest putting a month and year format within the naming of the file. This makes it easier to find your most recent files, especially if there are reports that must be pulled on a monthly basis. Labeling master folders by year and then breaking them down per subfolders is an easy way to catalog and find your data easier and more efficiently.

Guidelines for data classification:- 1. Conduct a sensitive data risk assessment. 2. Develop a formalized classification policy. 3. Categorize the types of data. 4. Discover the location of all data. 5. Identify and classify data. 6. Enable effective data security controls. 7. Monitor and update the classification system.

Data classification helps to protect your valuable data and improves data security. Once you identify the different data types in your network, you can separate your sensitive data from general data. In turn, this allows you to: Prioritize your security measures.