Tuesday, 27 April 2021

Data Classification (MIS 27.04.2021)

Data Classification

Data classification is the process of organizing data into categories that make it is easy to retrieve, sort and store for future use.

A well-planned data classification system makes essential data easy to find and retrieve.

 

Data classification is the process of organizing structured and unstructured data into defined categories that represent different types of data. Standard classifications used in data categorization include:

·                  Public

·                  Confidential

·                  Sensitive

·                  Personal

Sensitive data is a general term representing data restricted to use by specific people or groups. Sensitive and confidential data are often used interchangeably. Examples of sensitive data include intellectual property and trade secrets.

 

Data Classification is a data organization process into various categories that helps with both protection and general usage of such data. The very purpose of a classification process is to make your data easily locatable and retrievable without needing to interrogate it again. There are three main fields that rely heavily on a data classification as a process:

·                  Data security;

·                  Risk management;

·                  Compliance.

As the definition suggests, data classification is all about making data easy to find and track via the tagging process (i.e., within metadata properties). The same process also includes finding out and deleting data duplicates to save both storage costs and backup time. The entire data classification process may sound complicated, but it still has to be properly understood by organization’s leaders to make correct data-related decisions.

Data classification is an approach to identifying, protecting and managing information which has rapidly become best practice. Implemented as part of a layered security strategy, it enables an enterprise to defend itself against a variety of threats – from aggressive outsiders to untrained or well-meaning insiders – while unlocking the full potential of its data to drive innovation and productivity. At its simplest level, data classification is “the process of organising data into categories for its most effective and efficient use”.

 

Purpose of data classification

On top of making data easier to locate and retrieve, a carefully planned data classification system also makes essential data easy to manipulate and track.

Confidentiality. A classification system that values confidentiality above other attributes will mostly focus on security measures, including user permissions and encryption.

Integrity of data. A system that focuses on data integrity will require more storage, user permissions and proper channels of access.

Availability of data. When security and integrity do not need to be perfected, it is easiest to make data more easily accessible to users.

Data classification helps you understand what types of data you store and where that data is located.

1. Informs risk management, legal discovery and regulatory compliance processes

2. Helps prioritize security measures

3. Improves user productivity and decision-making by streamlining search and e-discovery

4. Reduces data maintenance and storage costs by identifying duplicate and stale data

5. Helps IT teams justify requests for investments in data security.

 

The primary objectives of data classification are:

1. To consolidate the volume of data in such a way that similarities and differences can be quickly understood. Figures can consequently be ordered in sections with common traits.

2. To aid comparison.

3. To point out the important characteristics of the data at a flash.

4. To give importance to the prominent data collected while separating the optional elements.

5. To allow a statistical method of the materials gathered.

 

Importance of data classification

Data classification is a way to be sure that a company or organization is compliant with company, local or federal guidelines for data handling and a way to improve and maximize data security.

 

Benefits of data classification

Using data classification helps organizations maintain the confidentiality, ease of access and integrity of their data. It also helps to lower the danger of unstructured sensitive information becoming vulnerable to hackers, and it saves companies from steep data storage costs. Storing massive amounts of unorganized data is expensive and could also be a liability.

More broadly, data classification helps organizations improve data security and ensure regulatory compliance.

Taking a user-driven classification solution approach allows controls, rules and policies to be consistently enforced throughout the organisation. It also delivers additional benefits:

 

Use Metadata to Protect Critical Data Through Its Journey

As well as shielding the business from hacker activity, the classification of data guards against accidental data loss from within the organisation. The metadata tag directs the actions of other downstream enterprise security and data management solutions – triggering rules so that, for example, an email gateway will automatically encrypt any file marked Confidential, while a data loss prevention (DLP) solution will block employees from uploading the file to a cloud file share service. The approach also enhances the effectiveness of security incident and event monitoring (SIEM) tools, allowing unusual and potentially risky user behaviour to be detected early on. If a user is consistently downgrading files from Confidential to Public, for example, or is copying sensitive documents to a storage device, this will be flagged up. The issue can then be addressed through training, disciplinary procedures or strengthening of policy.

 

Meet Regulatory Requirements and Demonstrate Compliance

Regulatory violations can lead to crippling fines, huge post event clean-up costs in the case of a breach and even criminal charges. Classifying data makes it easier for a business to meet the data governance requirements of the Data Protection Act, the European General Data Protection Regulation (GDPR), the Sarbanes-Oxley ActHIPAA and ITAR, for instance. The embedding of the classification label as metadata within files allows an enterprise to audit exactly who is accessing sensitive information, and keep a detailed trail of any policy violations or unusual behaviour. In addition to enabling potential breaches to be rapidly identified and addressed, this can be used to prove to the board, industry bodies and regulators that information is being appropriately controlled and documented.

 

 User-driven Classification

The implementation of a user-driven classification process helps to build a culture of security awareness across the organisation. It puts the onus of protecting data on everyone who handles it, ensuring that all employees understand the value of the information they work with on a daily basis, and know how to treat it. Data classification tools that incorporate the labelling of messages, documents and files into employees’ routine work processes, meanwhile, will help to drive the right behaviours.

 

Facilitate Safer Collaboration

Data classification provides organisations with a means of building security into the corporate culture in a way that fosters, rather than inhibits, the power employees have to work in more productive and agile ways. Because the protection travels with the individual pieces of data on their ‘journey’, systems and databases can be safely integrated, and ideas and information shared freely between people, without exposing data to unauthorised access or use.

 

Manage and Use Data More Effectively

Before you can make full use of your data you need to know what you’ve got and where it is. The huge volume of unstructured data that organisations hold – such as email messages, Word documents, PowerPoint decks, Excel files, images and videos – make this increasingly difficult to get a grip on. Classifying data makes it possible to establish exactly what is there, where it is stored, and how valuable it is. It also helps the business to identify what can be archived or deleted, and so avoid the high protection, storage and retention costs associated with hoarding vast amounts of data.

 

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