In today’s tech-enabled world, the amount of data generated is simply overwhelming for most organizations, and it is impossible for professionals to make use of manual, survey-based approaches to stay on top of an ever-changing sea of data. Organizations frequently purchase data from third parties to enhance the profiles of their existing customers and add to the information about their target audiences.
In the case of mergers and acquisitions, completely unknown data sets may be dumped into data lakes, and data transfer agreements may also occur between business partners. In reality, nobody really knows the data that they possess, and if they do know about it, the information they have about that data is obsolete within a period 24 hours as data is always changing. Most organizations face challenges as they struggle to meet new and updated privacy requirements.
The fear of data misuse, after implementation of regulations such as the GDPR and the new California privacy law, has triggered reactions across various sectors as organizations search for ways to lock down their data by default. Despite this reaction not being a viable solution, it is the only way organizations know to protect personal information.
What Is Data Privacy?
Data privacy is a part of data protection and comprises the proper handling of data. It includes methods of data collection, storage, and sharing with third parties, and also, compliance with any applicable privacy laws, such as GDPR, GLBA, HIPAA, or CCPA, among others. As much as data privacy is about the proper handling of data, the public expectation of privacy is of equal importance. While processing personal customer data, organizations must make sure that they protect the privacy preferences of each individual.
What Is Data Privacy Automation?
The process of automating the handling of data, notice, consent, and regulatory obligations is known as data privacy automation. While none of the GDPR, the HIPAA, or the CCPA define what they mean by data privacy, they contain a set of best practices that spell out the rights of consumers and businesses. Data privacy automation is of utmost importance as each law is different in their definition of privacy, and the risk of incompliance is much greater when done manually.
Compared to data privacy automation, the problem with manual compliance of these laws is that the practical implications are incredibly complex. The GDPR looks to present a compromise between the values of many varied nation-states and their different systems. Due to this, data scientists and managers subject to the law or find it incomprehensible. According to these data professionals, absolute compliance is still a doubt. Therefore, data privacy automation presents itself as a golden opportunity for organizations to remain compliant with these laws.
Importance of Data Privacy Automation
In this data-ruled age, the true value of a company lies in its collection of customer data. This actually translates to data being viewed as a company asset that is worth collecting, storing, and, more importantly, protecting. However, the personal data of individuals was never the company’s to keep. Data privacy laws provide consumers with the right to take back ownership of their data and the right to be forgotten.
If companies want to hold onto customer data, they must maintain trust in their customers, which is possible by demonstrating transparency; and a way to do so would be data privacy automation. Open communication such as what data is collected, for which purpose, who processes it, and more, instill trust in customers. GDPR represents a set of the most wholesome data protection laws, and the violation of customer rights can result in huge fines, all to protect the privacy of an individual.
To steer clear of any trouble, organizations must take proactive steps and measures such as resorting to data privacy automation and implementing data safeguards and protection software that help guide privacy programs, automate processes and navigate through applicable data privacy laws.
Data Privacy vs. Data Security
For those that think data security and data privacy are one and the same, this would come as quite a revelation: They aren’t. Organizations are often of the belief that securing sensitive data automatically makes them compliant with data privacy regulations. These two are vastly distinct as data security protects data from leaks caused by external hackers or malicious insiders, whereas data privacy governs the collection, sharing, and usage of data.
To efficiently comply with data protection laws and protect data, organizations need a combination of data privacy and data security. No extent of data security could equate data privacy. However, this said, while data security can exist without data privacy, it is not possible the other way around.
Timeline of Data Privacy Regulations
Data Privacy Best Practices
So, how do individuals and organizations ensure data privacy? Is data privacy automation the key? Mentioned below are some best practices for businesses and consumers to stay compliant with data regulations.
- Businesses must ensure that every employee is aware of data security and privacy concerns and techniques. This data privacy training could be integrated into any general training program and should be made a part of the onboarding process.
- Take advantage of free security tools for data privacy automation that are available in the market, such as encrypted storage solutions, VPNs, and password managers. These tools help in drastically decreasing an organization’s vulnerability to malicious attacks and are also easy to use and install.
- Have an employee, or a team in place, depending on the size and preference of the organization, to monitor the organization’s network for any suspicious activity and to maintain data privacy automation. This enables organizations to detect attacks in their early stages and help reduce any further damage.
- A trivial mistake most organizations make is underestimating the interest of hackers in their organization. Regardless of whether the organization is small or just a start-up, attacks and breaches affect organizations irrespective of their size.
- Enforce a ‘zero trust’ policy that restricts access to the entire network by segmenting network access depending upon authentication, user permission, and verification, and isolating applications. This data privacy automation approach mandates the verification of authorized entities and is essential for organizations today.
- Individuals can take a few steps to improve the privacy of their data. To begin with, they can familiarize themselves with data privacy automation tools available in the market, such as a VPN to encrypt their internet connection and a password manager to enhance online account security.
- Make use of the multi-factor authentication process for additional security and ensuring that important accounts aren’t easily hacked in the case of a password being leaked.
- Keep all IoT devices updated with the latest security software to steer clear of spyware.
- Frequently back up data to keep hold of data that may be compromised or lost.
General Functions Organizations Perform to Maintain Data Privacy and Data Privacy Automation
The volume, variety, and frequency of big data are simply going haywire in traditional privacy functions. Organizations are resorting to functions such as the following to resolve these problems.
Organizations have begun mapping structured and unstructured, on-premise and in-the-cloud data while at rest, and also while streaming. Companies have started to implement data privacy automation solutions that find where data resides in their organizations.
Creation of Audit Trails
Now, more than ever, companies need to possess the ability to prove that the action they have taken on the data is the right one, with legislation such as the GDPR in effect. Data privacy automation software that automatically creates evidence of compliance and remediation efforts is highly sought after by companies. .
Personal Data Redaction
Companies make use of advanced data privacy automation tools to identify non-essential data versus essential data and redact any non-essential, personal data. It is vital for companies to redact or anonymize data through data privacy automation to ensure individuals cannot be identified in order to avoid penalties for non-compliance GDPR or any other legislation.
Privacy is the right of an individual to be left alone, and by leveraging data privacy automation, companies must strive to be as transparent as possible and efficient in the protection of data privacy of their consumers. Governments worldwide have recognized the right to data privacy and have formulated numerous data protection laws in accordance with it, which can best be followed by data privacy automation. During the initial adjustment period, regulatory authorities were understandably moderate whilst proposing GDPR fines, however, recent trends have shown that more considerable finds are being prepared for organizations these days.
While GDPR is not the first data privacy law, it is the first one that conveyed serious intent to control the unjust exploitation of personal user data by fining data processors and controllers accordingly. More important than the fines levied on organizations, GDPR has provided individuals with the power to regain control over their privacy. While creating business plans, marketing campaigns, and strategies, companies must learn to embrace the fact that they need to consider data privacy automation, not only because of heavy fines but more so because it is what their consumers expect.