The 7 data Privacy by Design principles and the single technology to combine them all

Tally Netzer

Tally Netzer

When GDPR came into force in 2018, it introduced a set of data privacy requirements that transformed how companies track and analyze user activity, communicate their privacy policies, and even design their solutions. Article 25, titled "Data Protection by Design and by Default," specifies the “appropriate technical and organizational measures” that companies are expected to implement.  

Luckily for businesses in Europe and beyond, the notion of privacy by design has been discussed over the years, long before it became mandatory. Essentially, it means that instead of adding privacy-focused elements as an afterthought, companies must consider privacy protection from the get-go and take it into account throughout the design process.    

One of the primary sources of information helping companies achieve this is the paper “Privacy by Design in Law, Policy and Practice,” which details seven fundamental principles. Today, we already know that data privacy is the focal point of all privacy protection efforts, by design or otherwise. That’s why we’ve decided to discuss these seven pillars while focusing on data privacy specifically.   

 The seven data privacy by design principles  

  1. Proactive, not reactive; preventive, not remedial: Instead of reacting to data breaches, companies need to design their data system to protect user privacy from being breached as well as inherently minimize the damage when a breach occurs. The data architecture can be instrumental in helping to secure customer data. When user data is compartmented and encrypted at the individual customer level, data exposure is minimal even in the case of a breach.
     
  2. Privacy as the default setting: Companies shouldn’t expect users to take any action to protect their data privacy. The basic business conduct and data management procedures should be private and secure. Easy to use Consent Management ensures users can make informed decisions regarding their private data.

  3. Privacy embedded into the design: Companies should focus on privacy rights from the very beginning of software application design, and along every step of the application lifecycle. It helps to be working with a solution that is both user-centric and secure, while providing the workflows and interfaces needed to design and run a privacy-focused operation.

  4. Full functionality: Businesses and customers must never compromise their needs because of data privacy requirements. Professionals shouldn’t have to jump through hoops to remain compliant, and users shouldn’t experience any lagging or limitations in order to stay protected. Building a secure data management environment, where businesses and their customers can continue operating freely, is essential. Ultimately, such a system would overcome the underlying complexity of siloed applications and customer data fragmentation, to provide a seamless experience for the customer  promoting trust and regulatory compliance.

  5. End-to-end security: To ensure that a company’s entire lifecycle protects user’s data privacy, companies must operate within a secure environment and conduct an ongoing data privacy audit, even when customers aren’t actively using the system. Private customer data needs to remain secure at rest and in use. Role-based privileges should be used to securely provide access on a need-to-know basis.

  6. Visibility and transparency: First, companies must offer users a clear idea of the data privacy protection measures they use and the information they collect, analyze, and share. They should then be able to easily answer any user queries by implementing a data fabric that allows them to instantly fetch all the relevant, most updated data regarding a specific user. For large enterprises, dealing with many legacy systems and data islands, this is a tough directive. Especially, in high-volume scenarios, where manual processes cannot scale. To deliver timely responses to Data Subject Access Requests (DSARs), data privacy management solutions need more than data process automation. They need to automate the data processing itself.

  7. User-centric respect for privacy: Last but not least, businesses should view users as individuals and empower them to control their own data. Whether the user’s data is fragmented across 10 or 100 systems and/or databases, users should experience a consistent, holistic experience that reflects their choices and respects their privacy preferences. A holistic view of each individual customer privacy and consent preference would make delivering user-centric privacy simple and scalable.  

Privacy by Design is critical not just because it saves time and prevents costly breaches and fines, but also because it sends an important message. K2View’s compliance management software embodies the Data Privacy by Design principles – based a single secure Micro-Database™ that delivers a holistic, privacy-focused view of each individual customer. Proven in tier-1 telcos and enterprises, this solution overcomes underlying system complexity to deliver scalable privacy-focused deployments.