Key Differences Between Data Protection and Data Privacy

Data breach incidences are commonplace in today’s business landscape, with an increasing number of businesses and Big Data analytics companies struggling to navigate the situation to their advantage.

From an organization’s perspective, lost or stolen data could range from relatively benign/harmless records to strictly personal/confidential information. In any case, such instances of data exposure can have both negative financial impacts and cause significant reputational damage to the organization.

What further complicates the issue is the lack of understanding on users’ part about two of the core concepts associated with data storage – data protection and data privacy – and how they differ.

To make it simpler for you, this blog aims to shed some light on the concepts of data protection and data privacy, the key differences between them, and how they can impact the best Big Data companies in the long run.

Understanding Data Protection and its Importance

Data protection is essentially the set of strategies and processes used to secure the integrity, availability, and privacy of data. Simply put, data protection policies in any organization revolve around safeguarding the data and important information against unauthorized access.

Recent statistics suggest that almost 90% of companies were working on doubling up their cybersecurity budgets last year, thus giving more importance to safeguarding their data against cyber attackers, hackers, and anyone else with malicious intent.

This clearly highlights the importance of data for any Big Data analytics company that works on sensitive/personal information related to customers, suppliers, or other stakeholders.

Having a powerful data protection plan can be instrumental in preventing data loss and theft in any form. Since the key aim of data protection is to secure an organization’s data, a well-crafted and successful data protection strategy also helps you eliminate the instances of unexpected data breaches or disasters, thus keeping data loss to a minimum.

Understanding Data Privacy and its Importance

Data privacy is a concept that primarily focuses on how personal data is collected, used, and shared. It is important to note that data privacy is mainly a policy-driven or governance initiative, and regulations/laws addressing data privacy can vary based on which state/country you are in.

Data privacy is important for top data science companies because countries across the world are realizing the role of strict guidelines in protecting personal data privacy and how it is in the best interest of both organizations and individuals.

Having a proper data privacy policy in place allows top Big Data companies to prevent unwanted notorious elements from accessing and using sensitive/personal data with malicious intentions.

To date, the European Union’s General Data Protection Regulation (GDPR) is the strictest data privacy regulation, with several countries following suit and modeling regulations after the privacy mandates of the GDPR.

How is Data Privacy Related to Data Protection?

Often mistaken for the same concept, data protection and data privacy are different from each other. What connects them, however, is the fact that data privacy is one of the subsets of data protection.

Safeguarding any kind of personal or sensitive personal data is the focus of data protection, whereas data security is the mechanism that mainly works to ensure data privacy.

Since data privacy is more about the policy and not a type of technology, data protection solutions in the best Big Data companies are required for keeping sensitive data secure in any organization.

In short, data privacy is about establishing what information should be protected, and data protection is about the safeguarding mechanisms that should be in place.

Data Protection and Data Privacy: Key Differences

Understanding the key differences between data protection and data privacy thoroughly is important to keep your organization and its data safe from attackers.

While data protection primarily focuses on preventing unauthorized access, data privacy aims to ensure that there is authorized access and mainly comes down to knowing which parties have access to the data legally.

Among the other key differences between the two are:

Separate Responsibilities 

Whether you wish to implement data protection or data privacy in your organization, it is important to understand that they both have separate responsibilities.

Data privacy is mainly responsible for clarifying policies in top data warehouse companies about data use when it’s shared in an organization and fulfilling different regulations set by the respective industry/government, thus protecting your organization from getting into any legal messes at a later stage.

Data protection, on the other hand, is responsible for establishing various mechanisms that safeguard data. Among these mechanisms are procedures/tools required to ensure that the set regulations and policies are followed.

By having data protection laws in place, you can be adequately prepared to prevent criminals or suspicious elements from accessing any sort of sensitive data.

Varied Safety Goals

Another key difference between data protection and data privacy is the kind of safety they offer your organization.

While data protection largely focuses on offering safety from online criminals and hackers by putting in place various tools/procedures required to stop them from compromising data security, data privacy offers greater protection against any kind of unauthorized sales.

Unlike data protection, data privacy deals with managing the people who have access to an organization’s sensitive data, thus protecting it from being shared/sold by bad elements. This, in turn, ensures that only thoroughly vetted parties or users can access important organizational data.

Focus Mechanisms vs. Policies

While the main focus of data privacy in the best Big Data companies is on defining the people who have access to important data, data protection focuses on applying such restrictions on data access.

In simpler terms, data privacy is more about the policies, whereas data protection is all about the mechanisms, tools, and processes.

It is also important to keep in mind that the way you can not restrict unauthorized users while creating data privacy guidelines, and you also can’t restrict access with data protection while leaving confidential data vulnerable.

Dependency: Data Protection Doesn’t Guarantee Data Privacy and Vice-Versa

When you have a data protection plan in place, it doesn’t necessarily guarantee that you’ll also have data privacy. Similarly, having robust data privacy protocols does not mean you’ll have effective data protection.

For instance, there is every possibility that top data engineering companies may struggle to block unauthorized users from accessing their critical data even after putting strict data privacy guidelines in place, mainly due to a lack of data protection protocols.

Likewise, there are chances that they might have data protection protocols in place but leave confidential or sensitive information vulnerable to unauthorized users due to the lack of proper data privacy standards.

This simply means that data privacy and data protection are not exclusive of each other, and you need both to secure your data.

By having data protection and data privacy laws, top data warehouse companies can ensure to put in place both technical and legal controls that are of utmost importance to safeguard data from suspicious elements.

Responsibility: Company vs. Users 

Having clarity on who is responsible for controlling the protection vs. privacy of data is very important when your organization collects data from users and customers.

As an organization, when you collect/store data, users are typically in control of data privacy because it is the user who works on everything, from what data is being shared and who it is shared with.

Organizations, on the contrary, are mainly responsible for safeguarding the data shared with them by the users. Since users are in a better position to confirm the kind and level of security they wish to have on the data, top data engineering companies are required to have the necessary data protection tools and mechanisms to meet such security expectations and ensure seamless data integration across multiple sources.

Meeting those responsibilities allows your organization to be in a better position to avoid any kind of legal as well as credibility troubles.

To Conclude

In a nutshell, data protection is all about securing your data against unauthorized access. Data privacy, in contrast, is more about authorized access in terms of who has it and who defines it.

So, while data protection is essentially a technical issue for organizations, data privacy is more policy-driven or legal.

At 4Seer, we understand that data protection and data privacy are two concepts that go hand in hand. We have several years of experience and professional expertise in helping you ensure ultimate data protection and privacy to bring the concept of discovery through data science to fruition.

Contact us today to know more about how 4Seer can offer greater data protection and privacy for the safety of your organizational data.