Personal, sensitive and anonymous data: understand what it is and how to manage it in a data protection plan
Posted: Thu Jan 23, 2025 5:54 am
Thus, it is possible to adapt to the new law, especially for companies with a lot of activity in Digital Marketing .
With digital transformation , the importance of data has become even more relevant, with inevitable dialogues on the topic. Some of these assets are generated from the use of computer systems, by people. However, there is also data concerning the personal lives of users , which are used in applications for certain purposes. We call these personal data.
In recent years, the debate on technological developments and the business owner database processing of personal data has advanced significantly. We have more qualified people in companies and in the marketing sectors , aware of the limitations and ethical principles behind the concept of privacy .
To continue to better understand the relevance of personal and sensitive data in a post-GDPR dialogue context, read on!
In this article, we will define data in its categories and how it relates to the new law, exploring topics such as:
What is personal data?
What is sensitive personal data?
What is anonymous data?
What is the difference between personal, sensitive and anonymous data?
What is this data used for under the GDPR?
What is personal data?
The General Data Protection Law was created, above all, with the firm intention of acting on the protection of this category of data. Therefore, personal data must be adequately defined so that we understand the object of study and debate of the new law.
Personal data is data that enables the identification of a specific person . It is an asset that, whether isolated or cross-referenced, enables an individual to be found and referred to. In this sense, it is a unique reference that distinguishes a human being from a mass of people, in order to enable a specific action.
A common example in Mexico is the ARCO Rights , which states that every person has the right to protect their personal information and, likewise, the right to access, rectify, cancel and oppose it.
In Digital Marketing, an email can be considered personal data, as it is unique and is accessed by one person with a private password. A cell phone number is also a great example. This information allows the company to speak directly to the customer and segment actions based on an ID.
Other interpretations understand personal data as data that directly impacts the individual when used for suspicious purposes . However, if identifiable data is used for a crime, it is easy to understand how this generates a direct effect on the identified person, since he or she becomes the subject of the incident.
Other examples include: name and surname, ID number, electronic address data (IPs), age, address, tastes, preferences, habits, biometric data, among others.
Source: ICR Evolution
What is sensitive personal data?
In the LGPD and in discussions about privacy, new categories of data have emerged. One of them is sensitive data: these are those that can be used for some kind of discrimination or direct harm to the person based on judgments from a moral perspective.
Examples include data on political orientation, sexual life and health, biometrics, religious orientation and others . This is private data and therefore even more specific.
This is information that requires greater secrecy and even stricter care on the part of those who process it, according to the GDPR, as we will see in the last topic of this article.
What is anonymous data?
Anonymous data is personal data that has undergone an anonymization process. That is, it is processed in such a way as to lose a direct connection with a specific individual. In this sense, data that has no specific impact on a particular human being is used.
We easily understand how anonymization can represent both the possibility of exploring data without having to deal with GDPR legislation and the impossibility of managing data for the specified purpose. After all, data is organized in general versions, with features to prevent direct access, which can lead to the loss of the value of the information for use.
For example, for Marketing, anonymous data can help when needed to assess customer profile information or understand general market trends. In the definition of Buyer Persona in Digital Marketing, for example, it is possible to conduct a general survey on customer preferences, pains and habits anonymously, in order to arrive at a specific and semi-fictional profile of the ideal customer .
In this case, it is not important to know who the customers who responded are, but what they actually said in order to establish the characteristics that will support the actions and campaigns. It is therefore easier to adapt to the GDPR, since this data does not generate as much impact for the owners.
However, when it comes to looking for leads for a subsequent conversation leading to a purchase , they are not useful. In this scenario, having personal data and direct access is essential.
One of the characteristics of anonymous data is, precisely, the ability to prevent it from being reverted to personal data after a transformation process. In other words, data that cannot be re-identified.
Anonymous data is therefore different from pseudonymous data. Data pseudonymisation involves making data anonymous but with the possibility that it can be made personal again at a later time.
Now, let's look at some data anonymization methods to better understand how this type of information works.
Anonymization
A common type of process is one that completely transforms the data, removing links to the individual, with no reversal, as we have already mentioned.
The complete removal of a column containing personal information in a database, for example.
Suppression
Deletion uses fixed data to replace identifiable parts of a database. Examples include the use of asterisks or other standardized forms of data.
Generalization
Generalization involves transforming specific data into general categories to eliminate individual connections. An example of this is transforming information about a customer into data about a class or group (such as the classic definition of an audience).
This is a good strategy, as it allows for active use of data, without it being personal.
Pseudonymization
A common method of pseudonymization is to use a parallel table to the one containing the personal data. In parallel tables, the data is anonymized, but it allows a connection to the original data through a key, for example.
Cryptography
Another very popular feature is encryption. This approach relies on the use of public and/or private keys to allow access to the original data. After cryptographic transformation, protected anonymous data is generated, which can only be unlocked with keys.
What is the difference between personal, sensitive and anonymous data?
When we put these three definitions into perspective, we can draw some interesting conclusions. Personal data is the most general, as it even sets the main standardization target.
Sensitive data is different, as it is more specific and delicate when it comes to moral assessment, but it falls within the concept of personal data. Sensitive personal data may involve some kind of discomfort that can generally be avoided with personal data.
For example, someone may discriminate against a person based on their religious views, political preferences or aspects of their private life. Vacant positions, projects and opportunities or confirmations in protocols/applications may also be rejected.
Security and privacy laws are very concerned about events that depend on this specific personal data. Therefore, more care must be taken with sensitive data, after all, non-discrimination is one of the principles of the law.
Anonymous data, on the other hand, can be understood as the opposite of personal data, as we have already discussed here. At no point can it be re-identifiable, as this defeats the very idea of anonymity. In this sense, anonymous data is very different from sensitive data.
Pseudonymized data therefore falls somewhere between personal (identifiable) data and anonymized data. It goes through a transformation process, but it is not radical to the point of making that data impossible to reverse. Generally, it is still under the protection of privacy and security laws.
What is this data used for under the GDPR?
The General Data Protection Regulation has recently shed light on the notions of personal, sensitive and anonymous data. It also established standards and requirements that must be considered by all types of companies, since anyone who processes data is subject to this law.
Personal data should be processed only for legal reasons. One of them is the consent of the interested party, which must be clear, provided after demonstrating the real purpose of the use of the data.
Other requirements are:
legal obligation,
protection of the life of the holder,
implementation of public policies,
credit protection,
inter alia.
Sensitive data can also only be handled under pre-established conditions, such as studies for research organizations, exercising rights, fraud prevention, protection of life, among others. In other words, special care is needed, as we have already discussed.
Anonymized data is, by definition, exempt from GDPR . If the data is truly non-identifiable, there is no need to pay attention to the requirements of the law, since it is not personal data.
In addition, some of the anonymization techniques mentioned above are adopted as a solution to manage the problem of adaptation to the standard.
What is being debated a lot these days is the level of anonymization that is possible with current techniques. There are researchers who support the idea that the methods never succeed in reversing this link with the original data, so they always become pseudo-anonymous. In this case, it is essential to understand the law and comply with it.
In addition to these general considerations, the GDPR proposes some structural concerns that should be part of the company's mindset and culture . First, it is necessary to stipulate a very specific and clear purpose for the use of the data and express it unambiguously to the data subjects. Once this purpose is established, it is only necessary to retain the data until it is fulfilled.
Another important point is free access. The data subject must be free to consult his data, modify it, transfer it to other databases and even delete it at any time, even after having given his consent. This is the great differential issue of privacy laws such as the GDPR (General Data Protection Regulation) and the laws of each country on the subject: the total focus on the data subject.
The following rights of individuals with regard to their data are currently officially recognized:
to be forgotten;
right to information;
right of access;
to request changes to your data;
to withdraw consent;
right to object;
to data portability.
Dedicated professional
In addition, the company should establish an internal general authority to oversee the data, and that person should report to general and external bodies. In some cases, this is a Data Protection Officer.
In cases of incidents involving personal or sensitive data, it is necessary to notify the data subjects and the main agencies, with a clear definition of the measures that will be taken for the intervention. It is essential to be clear about what will be done.
If companies do not properly manage security and privacy, they can be fined up to MX$27 million , or they can suffer warnings and data blocking, each action depending on the level of the problem and the impact on data subjects.
In the modern data-driven world, concern for laws and privacy must be central. After all, for a conscious and healthy use of these assets, companies must resort to the principles of the law and actively care about the rights of their customers, as this translates into trust in the business relationship.
From that point on, data must be carefully managed throughout its lifecycle. It will be essential to map it by use and seek an overview of how these assets are being applied, so that a complete and safe inspection is possible.
With digital transformation , the importance of data has become even more relevant, with inevitable dialogues on the topic. Some of these assets are generated from the use of computer systems, by people. However, there is also data concerning the personal lives of users , which are used in applications for certain purposes. We call these personal data.
In recent years, the debate on technological developments and the business owner database processing of personal data has advanced significantly. We have more qualified people in companies and in the marketing sectors , aware of the limitations and ethical principles behind the concept of privacy .
To continue to better understand the relevance of personal and sensitive data in a post-GDPR dialogue context, read on!
In this article, we will define data in its categories and how it relates to the new law, exploring topics such as:
What is personal data?
What is sensitive personal data?
What is anonymous data?
What is the difference between personal, sensitive and anonymous data?
What is this data used for under the GDPR?
What is personal data?
The General Data Protection Law was created, above all, with the firm intention of acting on the protection of this category of data. Therefore, personal data must be adequately defined so that we understand the object of study and debate of the new law.
Personal data is data that enables the identification of a specific person . It is an asset that, whether isolated or cross-referenced, enables an individual to be found and referred to. In this sense, it is a unique reference that distinguishes a human being from a mass of people, in order to enable a specific action.
A common example in Mexico is the ARCO Rights , which states that every person has the right to protect their personal information and, likewise, the right to access, rectify, cancel and oppose it.
In Digital Marketing, an email can be considered personal data, as it is unique and is accessed by one person with a private password. A cell phone number is also a great example. This information allows the company to speak directly to the customer and segment actions based on an ID.
Other interpretations understand personal data as data that directly impacts the individual when used for suspicious purposes . However, if identifiable data is used for a crime, it is easy to understand how this generates a direct effect on the identified person, since he or she becomes the subject of the incident.
Other examples include: name and surname, ID number, electronic address data (IPs), age, address, tastes, preferences, habits, biometric data, among others.
Source: ICR Evolution
What is sensitive personal data?
In the LGPD and in discussions about privacy, new categories of data have emerged. One of them is sensitive data: these are those that can be used for some kind of discrimination or direct harm to the person based on judgments from a moral perspective.
Examples include data on political orientation, sexual life and health, biometrics, religious orientation and others . This is private data and therefore even more specific.
This is information that requires greater secrecy and even stricter care on the part of those who process it, according to the GDPR, as we will see in the last topic of this article.
What is anonymous data?
Anonymous data is personal data that has undergone an anonymization process. That is, it is processed in such a way as to lose a direct connection with a specific individual. In this sense, data that has no specific impact on a particular human being is used.
We easily understand how anonymization can represent both the possibility of exploring data without having to deal with GDPR legislation and the impossibility of managing data for the specified purpose. After all, data is organized in general versions, with features to prevent direct access, which can lead to the loss of the value of the information for use.
For example, for Marketing, anonymous data can help when needed to assess customer profile information or understand general market trends. In the definition of Buyer Persona in Digital Marketing, for example, it is possible to conduct a general survey on customer preferences, pains and habits anonymously, in order to arrive at a specific and semi-fictional profile of the ideal customer .
In this case, it is not important to know who the customers who responded are, but what they actually said in order to establish the characteristics that will support the actions and campaigns. It is therefore easier to adapt to the GDPR, since this data does not generate as much impact for the owners.
However, when it comes to looking for leads for a subsequent conversation leading to a purchase , they are not useful. In this scenario, having personal data and direct access is essential.
One of the characteristics of anonymous data is, precisely, the ability to prevent it from being reverted to personal data after a transformation process. In other words, data that cannot be re-identified.
Anonymous data is therefore different from pseudonymous data. Data pseudonymisation involves making data anonymous but with the possibility that it can be made personal again at a later time.
Now, let's look at some data anonymization methods to better understand how this type of information works.
Anonymization
A common type of process is one that completely transforms the data, removing links to the individual, with no reversal, as we have already mentioned.
The complete removal of a column containing personal information in a database, for example.
Suppression
Deletion uses fixed data to replace identifiable parts of a database. Examples include the use of asterisks or other standardized forms of data.
Generalization
Generalization involves transforming specific data into general categories to eliminate individual connections. An example of this is transforming information about a customer into data about a class or group (such as the classic definition of an audience).
This is a good strategy, as it allows for active use of data, without it being personal.
Pseudonymization
A common method of pseudonymization is to use a parallel table to the one containing the personal data. In parallel tables, the data is anonymized, but it allows a connection to the original data through a key, for example.
Cryptography
Another very popular feature is encryption. This approach relies on the use of public and/or private keys to allow access to the original data. After cryptographic transformation, protected anonymous data is generated, which can only be unlocked with keys.
What is the difference between personal, sensitive and anonymous data?
When we put these three definitions into perspective, we can draw some interesting conclusions. Personal data is the most general, as it even sets the main standardization target.
Sensitive data is different, as it is more specific and delicate when it comes to moral assessment, but it falls within the concept of personal data. Sensitive personal data may involve some kind of discomfort that can generally be avoided with personal data.
For example, someone may discriminate against a person based on their religious views, political preferences or aspects of their private life. Vacant positions, projects and opportunities or confirmations in protocols/applications may also be rejected.
Security and privacy laws are very concerned about events that depend on this specific personal data. Therefore, more care must be taken with sensitive data, after all, non-discrimination is one of the principles of the law.
Anonymous data, on the other hand, can be understood as the opposite of personal data, as we have already discussed here. At no point can it be re-identifiable, as this defeats the very idea of anonymity. In this sense, anonymous data is very different from sensitive data.
Pseudonymized data therefore falls somewhere between personal (identifiable) data and anonymized data. It goes through a transformation process, but it is not radical to the point of making that data impossible to reverse. Generally, it is still under the protection of privacy and security laws.
What is this data used for under the GDPR?
The General Data Protection Regulation has recently shed light on the notions of personal, sensitive and anonymous data. It also established standards and requirements that must be considered by all types of companies, since anyone who processes data is subject to this law.
Personal data should be processed only for legal reasons. One of them is the consent of the interested party, which must be clear, provided after demonstrating the real purpose of the use of the data.
Other requirements are:
legal obligation,
protection of the life of the holder,
implementation of public policies,
credit protection,
inter alia.
Sensitive data can also only be handled under pre-established conditions, such as studies for research organizations, exercising rights, fraud prevention, protection of life, among others. In other words, special care is needed, as we have already discussed.
Anonymized data is, by definition, exempt from GDPR . If the data is truly non-identifiable, there is no need to pay attention to the requirements of the law, since it is not personal data.
In addition, some of the anonymization techniques mentioned above are adopted as a solution to manage the problem of adaptation to the standard.
What is being debated a lot these days is the level of anonymization that is possible with current techniques. There are researchers who support the idea that the methods never succeed in reversing this link with the original data, so they always become pseudo-anonymous. In this case, it is essential to understand the law and comply with it.
In addition to these general considerations, the GDPR proposes some structural concerns that should be part of the company's mindset and culture . First, it is necessary to stipulate a very specific and clear purpose for the use of the data and express it unambiguously to the data subjects. Once this purpose is established, it is only necessary to retain the data until it is fulfilled.
Another important point is free access. The data subject must be free to consult his data, modify it, transfer it to other databases and even delete it at any time, even after having given his consent. This is the great differential issue of privacy laws such as the GDPR (General Data Protection Regulation) and the laws of each country on the subject: the total focus on the data subject.
The following rights of individuals with regard to their data are currently officially recognized:
to be forgotten;
right to information;
right of access;
to request changes to your data;
to withdraw consent;
right to object;
to data portability.
Dedicated professional
In addition, the company should establish an internal general authority to oversee the data, and that person should report to general and external bodies. In some cases, this is a Data Protection Officer.
In cases of incidents involving personal or sensitive data, it is necessary to notify the data subjects and the main agencies, with a clear definition of the measures that will be taken for the intervention. It is essential to be clear about what will be done.
If companies do not properly manage security and privacy, they can be fined up to MX$27 million , or they can suffer warnings and data blocking, each action depending on the level of the problem and the impact on data subjects.
In the modern data-driven world, concern for laws and privacy must be central. After all, for a conscious and healthy use of these assets, companies must resort to the principles of the law and actively care about the rights of their customers, as this translates into trust in the business relationship.
From that point on, data must be carefully managed throughout its lifecycle. It will be essential to map it by use and seek an overview of how these assets are being applied, so that a complete and safe inspection is possible.