Difference between Data Privacy and Data Protection
Last Updated :
15 Apr, 2025
The terms Data privacy and Data security are used interchangeably and seem to be the same. But actually, they are not the same. In reality, they can have different meanings depending upon their actual process and use. But they are very closely interconnected and one complements the other during the entire process. So, let's know how Data Privacy differs from Data Protection.
What is Data Privacy?
Data Privacy refers to the proper handling of data, which means how an organization or user determines whether or what data is to be shared with third parties. Data privacy is important as it keeps some data secret from others/third parties. So we can say data privacy is all about authorized access. It is also called data privacy.
For example: In a Bank, A lot of customers have their accounts for monetary transactions. So the bank needs to keep customers' data private so that customers' identity stays safe and protected as much as possible by minimizing any external risks and also it helps in maintaining the reputation standard of banks.
Why Data Privacy is Important?
Data privacy is a set of rules for collecting and handling data based on its importance and value. Personal health information (PHI) and personally identifiable information (PII) are commonly covered under data privacy laws. This includes financial information, medical records, social security or ID numbers, names, birth dates, and contact information. Data privacy helps to guarantee that sensitive information is only available to authorized parties.
Data Privacy Best Practices
- Do not use public Wi-Fi networks on your business devices.
- Understand how your current laws define personal information.
- Use adequate consent management when collecting data.
- Save only the most important information.
- Take strict measures to prevent human mistakes.
What is Data Protection?
Data Protection refers to the process of keeping important data safe. In simple it refers to protecting data against unauthorized access which leads to no corruption, no compromise, no loss, and no security issues of data. Data protection is allowed to all forms of data whether it is personal or data or organizational data.
For Example: A bank has a lot of customers, so the bank needs to protect all types of data including self-bank records as well as customer information from unauthorized accesses to keep everything safe and to ensure everything is under the control of bank administration.
Why Data Protection is Important?
Data protection refers to the process taken to ensure the privacy, availability, and integrity of sensitive data, and is frequently used interchangeably with the word 'data security'. These security measures are essential for organizations that gather, handle, or retain sensitive data. They work to avoid data corruption, loss, or harm. At a time when data collection and storage are growing at an unprecedented rate, a strong data protection strategy is critical. The major purpose of data protection is not just to preserve sensitive information, but also to keep it accessible and trustworthy, hence maintaining confidence and compliance in data-driven processes.
Principles of Data Protection
- Data Availability: Data availability guarantees that users can access and use the data they need to do business, even if it is lost or corrupted.
- Data Lifecycle Management: Data lifecycle management means automating the delivery of essential data to both offline and online storage.
- Information Lifecycle Management: Information lifecycle management means considering, recording, and protecting information assets against a variety of threats, including facility failures and disruptions, application and user errors, equipment failure, and malware and virus attacks.
Data Protection Best Practices
- Backup important data on a regular basis.
- Consider sending backup data to the cloud.
- Limit internal data access.
- Consider backing up data in a location other than your company's offices, as a major incident could destroy both the original files and the backups.
- Encrypt your data.
Difference Between Data Privacy and Data Protection
Data Privacy | Data Protection |
---|
Data Privacy refers to maintaining secrecy or keeping control of data access. | Data Protection is the process of protecting data from external risks such as corruption, loss, etc. |
It is all about authorized access means it defines who has authorized access to data. | It is all about unauthorized access means if anyone has not access to data then it keeps the data safe from that unauthorized access. |
Data Privacy is a legal process/situation which helps in establishing standards and norms about accessibility. | Data Protection is a technical control system which keeps data protected from technical issues. |
Data Privacy is the regulations or policies. | Data protection is the procedures and mechanism. |
It can be said as a security from sales means holding the data from shared and sold. | It can be said as s security from hacks means keeping the information away from hackers. |
Data Privacy controls are mainly exits at the end user level. The users knows which data is shared with whom and which data they can access. | Data Protection is mainly controlled by the organization or company end. They tech all the required measures to protect their data from being exposed to illegal activities. |
Data privacy teams are made of experts with law making, policies and some engineering experts. | Data protection teams are made of experts from technical background, security background etc. |
Conclusion
Data privacy and data protection are both important concepts to understand, while they both are all closely related, they represent very separate ideas and methodologies. Staying updated with best practices and upgrading your data policies can help protect you and your customers against cyberattacks and data breaches.
Similar Reads
Difference Between Data Privacy and Data Security
Data Privacy and Data Security are the two buzzwords that have become very crucial in modern society, especially in the current world the majority of organizations rely on the use of information. Even though these two concepts are interrelated, they differ in that one focuses on protecting informati
7 min read
Difference between Primary and Secondary Data
Researchers and analysts rely on two distinct types of data, namely primary data and secondary data. Primary data are unprocessed data that originate from the source and are collected or received by a researcher directly through surveys, interviews, or experiments. This is so unique and customized t
4 min read
Difference Between Traditional Data and Big Data
Data is information that helps businesses and organizations make decisions. Based on volume, variety, velocity, and mode of handling data, traditional data, and big data. It is quite helpful for organizations to understand these key dissimilarities to enable them to select the right approach in data
8 min read
Difference Between Data Encryption and Data Masking
Protecting private data has become compulsory for businesses. It is not just about following privacy laws. It is also about earning and keeping customers' trust. Two common methods to keep safe information are data encryption and data masking. While both try to keep data safe, they do it in differen
3 min read
Difference between Data Security and Data Integrity
Data protection and integrity have become very important in this modern world for organizations, companies, and even for the people. Unique, basic, and important to the theme here are two concepts Data Security and Data Integrity. Although both oversee separate ideas in the sector of data management
6 min read
Difference between Data Warehouse and Data Mart
Both Data Warehouse and Data Mart are used for store the data. The main difference between Data warehouse and Data mart is that, Data Warehouse is the type of database which is data-oriented in nature. while, Data Mart is the type of database which is the project-oriented in nature. The other differ
6 min read
Difference Between Data Mining and Data Visualization
Data mining: Data mining is the method of analyzing expansive sums of data in an exertion to discover relationships, designs, and insights. These designs, concurring to Witten and Eibemust be "meaningful in that they lead to a few advantages, more often than not a financial advantage." Data in data
2 min read
Difference Between Data Science and Data Visualization
Data Science: Data science is study of data. It involves developing methods of recording, storing, and analyzing data to extract useful information. The goal of data science is to gain knowledge from any type of data both structured and unstructured. Data science is a term for set of fields that are
2 min read
Difference between Data Warehousing and Data Mining
A Data Warehouse is built to support management functions whereas data mining is used to extract useful information and patterns from data. Data warehousing is the process of compiling information into a data warehouse. The main purpose of data warehousing is to consolidate and store large datasets
5 min read
Difference between Database and Data Structure
It is important to understand the fundamental difference between a database and a data structure. Basically, the database is used to store large amounts of data in a specific manner, that can be assessed, maintained, and updated by a database management system.There are many ways of organizing the d
4 min read