Companies have a wide choice of methods to deploy for the protection of data confidentiality. All of these techniques fall under one of two major categories: data anonymization and pseudonymization. Although these names are often used interchangeably, these are two different approaches to data security.
The following sections will show you more details about each of them, their significance for enterprises and the concept of the data anonymization tool.
The proper way of using the term data anonymization is to describe any technique that irreversibly de-identifies data.
As a rule, anonymization means removing any pieces of information from a data set that can be linked directly or indirectly to the personal identifiable information (PII).
Data anonymization has serious implications for companies. Since the records that can be recognized by data protection regulations as PII are no longer available and it is not possible to retrieve any PII using existing records, such a dataset does not have to comply with General Data Protection Regulations (GDPR).
Frequently, companies use a data anonymization tool to de-identify their data which permanently substitutes sensitive records with unrelated characters. One of the most accurate examples of data anonymization is blurring which creates random noise, usually for numeric values, that makes re-identification impossible.
Data pseudonymization is commonly referred to as one of the anonymization methods. From the point of view of GDPR, it is not correct. Data pseudonymization enables data retrieval and does not provide companies with total data protection.
Pseudonymization hides PII with various techniques like data masking or encryption. The first masks a fraction of records, preserving the usability of the rest of the information. The latter deploys ciphering for PII protection, however, data can still be deciphered with a decryption key.
Companies relying on pseudonymization have to comply with GDPR as they still store confidential information.
Companies are facing the dilemma of securing their data by means of pseudonymization or full protection of anonymization.
On the one hand, anonymization is more convenient as it helps organizations avoid many resource-consuming procedures for meeting the requirements of GDPR. They include information audits, defining a lawful basis for data processing, creating and managing documentation, enforcing quality control over security measures and much more.
On the other hand, anonymization deprives companies of the possibility of deriving business value from the sensitive data they collect. For many enterprises, information about their customers is one of the major resources for future development. With pseudonymization, organizations can still benefit from the data they collect, however, they should be very careful about compliance with GDPR.
Keep in mind that anonymization, although regarded as irreversible, sometimes might not be effective. For instance, a repetitive buying behavior of a customer such as making the same purchase every day at the same hour enables a re-identification of this person, even without PII.
Security with Data Anonymization Tool
To lessen the burden of PII management, companies rely on professional tools for data anonymization. They can be universal and applicable to different software or dedicated to a certain product.
The best choice of a data anonymization tool depends on the PII-processing software your company utilizes. Yet, no matter which one you select, make sure it supports both anonymization and pseudonymization.
If you have deployed a range of separate applications working with personal data, a less specific tool for anonymization might be a sensible choice for you. For companies relying on numerous interconnected apps working with the same records such as Microsoft Dynamics 365, using a specialized data anonymization tool, for example, the one offered by XPLUS, will be a better idea.