Common steps of data classification (MIS 28.04.2021)

Common steps of data classification

Most commonly, not all data needs to be classified, and some is even better destroyed. It is important to begin by prioritizing which types of data need to go through the classification and reclassification processes.

 

In addition, companies need to always consider the ethical and privacy practices that best reflect their standards and the expectations of clients and customers:

 

1. Scan. This step involves taking stock of an entire database and making a digital game plan to tackle the organization process.

 

2. Identify. Anything from file type to character units to size of packets of data may be used to sort the information into searchable, sortable categories.

 

3. Separate. Once the data is categorized with a system the data science professional implements, it can be separated by those categories whenever the system is called to bring them up.

 

Unauthorized disclosure of information that falls within one of the protected categories of a company's data classification systems is likely a breach of protocol and, in some countries, may even be considered a serious crime. In order to enforce proper protocols, the protected data needs to first be sorted into its category of sensitivity.

 

Data classification can be used to further categorize structured data, but it is an especially important process for getting the most out of unstructured data by maximizing its usefulness for an organization.

 

Types of data classification

 

Classification is an important part of data management that varies slightly from data characterization. Classification is all about sorting information and data, while categorization involves the actual systems that hold that information and data.

There are certain data classification standard categories. Each one of these standards may have federal and local laws about how they need to be handled. They include the following:

 

1. Public information. This standard is maintained by state institutions and subject to disclosure as part of certain laws. Eg. Mobile location data

 

2. Confidential information. This may have legal restrictions about the way it is handled, or there may be other consequences around the way it is handled. Eg. Defence data

 

3. Sensitive information. This is any information stored or handled by state institutions that include authorization requirements and other rigid rules around its use.

 

4. Personal information. Generally, peoples' personal information is considered protected by law, and it needs to be handled following certain protocols and rules for proper use. Sometimes there are gaps between the moral requirements and contemporary legislative protections for their use. Eg address & personal details of a person in bank.