What is Data Discovery and Classification, and Why is it Important?

We are all aware that data is a company’s most valuable resource. In a world where 2.5 quintillion bytes of data are produced every day, finding and identifying data is one of the most difficult procedures organizations deal with when implementing data protection strategies.

However, we are battling something a little bit bigger here: the average data breach cost increased from 3.86 million to 4.24 million in 2021, the highest average total cost in the report’s 17-year history. Although the numbers are not available yet, we can only assume that figure will increase for 2022.

Data protection is crucial to prevent the severe repercussions of data loss or compromise, however most firms are being held back by a significant issue: visibility. The majority of businesses are still having trouble understanding what data they have and where it is located. Luckily, that’s what Data Discovery and Classification is all about.

What is Data Discovery?

Data discovery is searching your whole environment for structured and unstructured data across your company. To find the whereabouts of sensitive and regulated data, you need to search the whole network, including file servers and hardware.

In summary, data discovery enables businesses to recognize, categorize, and track sensitive data, so they are able to understand where their data is stored fully. By doing this, businesses verify that they are complying with regulatory standards and that their data is better protected.

What is Data Classification?

Data classification is recognizing the different types of data that a company has found in addition to categorizing that data based on file type, content, and other metadata.

Sensitive data is more easily located and retrieved thanks to data classification, which also helps to reduce data duplication. For this reason, using it, compliance objectives are easier to meet by lowering storage and backup costs, increasing visibility into where data resides, and enabling businesses to categorize data according to the type of legislation it is controlled by.

5 Questions that help you better understand Data Discovery and Classification

1. What are the most typical difficulties in preventing breaches of sensitive data?

Data overexposure results in harsh penalties from regulators, decreased customer trust, and reputational damage. It is difficult and presents unique problems to secure sensitive data against breaches at the same time you are ensuring adequate data privacy and protection. The following list includes a few of the most typical difficulties:

• Data’s Exponential Growth: Organizations struggle to manage billions of data records due to the growing volume of data and ongoing technological advancements.
• Shadow Data: If organizations are unaware of sensitive data’s existence, it is difficult to protect it from dangers and breaches.
• Adherence Fatigue: The widespread use of digital technology and the growth of data have facilitated the establishment of stricter regulatory compliances. Companies wind up balancing different standards while upholding the laws they are responsible for.

2. What is the difference between Sensitive and Non-sensitive PII (Personally Identifiable Information)?

Information that is used to identify an individual is referred to as PII. Individuals may be identified using a single identifier or a combination of numerous identifiers via association with PII data. Sensitive or non-sensitive PII is categorized as follows:

• Sensitive PII: includes things like credit card numbers, passport numbers, financial details, and medical records. Such information hurts the person if it is revealed or leaked. As a result, it always must be gathered, saved and delivered securely.
  

  

• Non-sensitive PII: Information like date of birth, zip code, and religion that is readily accessible from public documents or websites is referred to as non-sensitive PII. Such data isn’t used to identify a specific person and therefore is able to be transferred in an unencrypted format.

3. What are the different types of Data Classification?

There are three different types of data classification, which are described below, depending on the demands of the business and the type of data:

• User-based Classification: Organizing data into categories depending on end-user judgment and knowledge.
• Content-based Classification: Reviewing and organizing files and documents.
• Context-based Classification: Organizing files into categories based on oblique clues such the creator, location, and application.

4. What are the effects of excessive data exposure in terms of compliance and regulations?

For a data security framework to be successfully implemented, compliance obligations need be met. A breach of compliance or excessive data exposure results in jail time and significant penalties.

Sensitive data collection, storage, and use are strictly governed by laws including the Health Insurance Portability and Accountability Act (HIPAA), California Consumer Privacy Act (CCPA), and General Data Protection Regulation (GDPR). Furthermore, authorities are the ones that impose penalties and expensive fines, as well as warnings and reprimands, for violations of these rules. Apart from the fines, excessive data exposure results in the firm losing customers and suffering reputational harm.

5. What is the difference between data privacy and data security?

Making sure that data is acquired, used, and shared securely is the main goal of data privacy. Data security, on the other hand, refers to the safeguarding of data from numerous internal and external dangers. Moreover, the standards for data privacy don’t need to be met by measures used for data security, and vice versa.

Data security policies call for taking precautions to protect data from malicious attacks and prevent unauthorized access to the collected data, whereas data privacy policies emphasize that data be obtained, processed, stored, used, and transmitted in accordance with the law and with respect for the privacy of the individual.

 

Finally, increasing your organization’s visibility into your data and assisting you in complying with rules are just two of the security advantages that come from combining data discovery and data classification. Because of this, any sensible data protection strategy must include data discovery and classification as a key element.

Do you need data discovery and classification specialists? Contact us! We have the talent you’re looking for.

About Centurion Consulting Group

Centurion Consulting Group, LLC, a Woman-Owned Small Business headquartered in Herndon,
VA conveniently located near Washington D.C., is a national IT Services consulting firm servicing
the public and private sector by delivering relevant solutions for our client’s complex business
and technology challenges. Our leadership team has over 40 years of combined experience,
including almost 10 years of a direct business partnership, in the IT staffing, federal contracting,
and professional services industries. Centurion’s leaders have the demonstrated experience over
the past three decades in partnering with over 10,000 consultants and hundreds of clients from
Fortune 100 to Inc. 5000 firms –in multiple industries including banking, education, federal,
financial, healthcare, hospitality, insurance, non-profit, state and local, technology, and
telecommunications. www.centurioncg.com.