A Guide to Data Minimization and How To Implement It
Harsh Sahu
CTO
May 2024 | 10 mins
In recent years, privacy has become crucial for businesses, required by regulations, and expected by customers. Previously, customers tolerated a lack of transparency, but now they demand that their data be used legally and appropriately, especially in AI applications. Data protection and data privacy has become the central theme of today’s data security landscape.
Privacy is now essential for building customer trust; 94% of organizations say that their customers would not buy from them if they did not protect data properly. That’s where data minimization as a data storage and management strategy comes into picture.
Data minimization is a principle which states that data controller (organizations or others entities processing personal data) should limit the collection of personal information to only necessary and relevant data to accomplish a specified purpose.
Article 5(1)(c) of GDPR says personal data shall be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed (data minimisation).
It also states that the data controllers should retain the personal data only for as long as is necessary to fulfil that purpose. In other words, data controllers should collect only the personal data they really need, and should keep it only for as long as they need it.
Simply put, data controllers should identify the minimum amount of personal data needed to fulfil the purpose. They should hold that much information, and nothing more.
328.77 million terabytes of data are created each day. Businesses are constantly facing the rising issue of privacy and data breach. This has significantly impacted business-customer relationship; with individuals now demanding more data protection regulations and privacy preserving techniques while collecting and processing their personal data.
Cisco’s Privacy Benchmark Study 2024 highlights the important of data privacy in the minds of customers for believing and trusting a business:
Though the above data highlights the overall demand of privacy and the need for data minimization, there are certain reasons which make this process a non-negotiable.
By adopting data minimization practices, organizations can significantly enhance their data security posture, maintain regulatory compliance, reduce costs, and build trust with their customers.
As state above, less data collected is more than enough. Organizations can maintain and comply with GDPR, while also protect privacy of individuals and gain their trust.
Few benefits of data minimization are highlighted below:
There are 8 key data minimization principles:
Gather only essential data for specific purposes. For example, if a service needs only an email, avoid collecting phone numbers or addresses.
Collect data for explicit, legitimate purposes only. Do not repurpose data, like using customer support data for marketing, without explicit consent.
Keep data only as long as needed. Regularly review and delete unnecessary data, such as inactive user accounts.
Ensure collected data is accurate and relevant. Regularly update personal information to maintain accuracy.
Protect identities by anonymizing or pseudonymizing data for analysis and research.
Implement strict access controls and security measures. Limit data access to necessary employees and use techniques like dynamic data masking.
Be clear about data collection practices. Provide privacy policies detailing what data is collected, why, and how it is used. Offer mechanisms for user inquiries and concerns.
Obtain explicit consent before data collection. Use opt-in mechanisms and provide easy ways for users to withdraw consent or delete their data.
By now you must have got the basic gist of how important data minimization principle is in terms of protecting privacy, maintaining a compliant business, and for data protection.
To start with, see the below figure, which states the rising rates of fines over the years for non-compliance with GDPR:
The other risks associated for no to minimum investment on data minimization are:
The EU’s GDPR data minimization is highlighted in article 5(1)(c), which states that personal data shall be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed. GDPR data minimization principles are amongst the most stringent rules and violation can lead to hefty fines for non-compliance.
The California Consumer Privacy Act, which was amended by the California Privacy Rights Act (CPRA), led the way in the U.S. with the first comprehensive state privacy regulation to give consumers enforceable rights over how – or whether at all – businesses collect, process, store, share or sell personal data.
The amendments under CPRA place more restrictions on collection, storage and use of sensitive personal information, and include data minimization and purpose limitation rules. CPRA data minimization rules mirrors GDPR data minimization principles to a large extent.
Data minimization practices should be part of the overall cybersecurity measures in an organization. This means ensuring that from the time personal data is collected till it is deleted, throughout its lifecycle, such data should have total integrity, accuracy, and no misuse.
Below is a step-by-step process of how you can implement a data minimization startegy without any blockers in your business operation:
#1 Conduct a Data Inventory and Audit
Step 1: Identify and catalog all personal data assets across the organization, including what data is collected, where it is stored, how it is used, and who has access to it. ( Read more on data discovery best practices )
Step 2: Perform a comprehensive audit to understand the current data landscape and identify unnecessary data that can be minimized.
#2 Define Data Minimization Policies
Step 3: Establish clear data minimization policies that outline the principles of collecting only necessary data, purpose limitation, and data retention limits.
Step 4: Ensure these policies comply with relevant data protection regulations such as GDPR, CCPA, and HIPAA.
#3 Implement Data Collection Controls
Step 5: Review and update data collection forms and processes to ensure only essential data is collected.
Step 6: Integrate automated controls and validations to enforce data minimization during data entry.
#4 Establish Data Retention and Deletion Protocols
Step 7: Define retention periods for different types of data based on legal requirements and business needs.
Step 8: Implement automated workflows to regularly review and securely delete data that is no longer needed.
#5 Anonymize and Pseudonymize Data
Step 9: Identify opportunities to anonymize or pseudonymize data to protect individual identities while retaining the utility of the data.
Step 10: Implement anonymization and pseudonymization techniques where applicable.
#6 Enhance Data Security and Access Controls
Step 11: Implement strict access controls to ensure that only authorized personnel have access to sensitive data.
Step 12: Use techniques such as dynamic data masking, encryption, and access logs to enhance data security.
#7 Educate and Train Employees
Step 13: Conduct training sessions for employees to raise awareness about data minimization principles and practices.
Step 14: Provide ongoing education on the importance of data privacy and security, and how to handle data responsibly.
#8 Monitor and Review Data Minimization Practices
Step 15: Establish a continuous monitoring system to track compliance with data minimization policies.
Step 16: Regularly review and update data minimization practices to adapt to new regulatory requirements and technological advancements.
#9 Implement a Data Governance Framework
Step 17: Develop a comprehensive data governance framework that includes data minimization as a key component. (Read more about Data Governance vs Data Security)
Step 18: Assign data stewards and governance teams to oversee the implementation and adherence to data minimization policies.
#10 Engage with Stakeholders
Step 19: Communicate the importance and benefits of data minimization to all stakeholders, including employees, customers, and partners.
Step 20: Involve stakeholders in the development and refinement of data minimization practices to ensure alignment with organizational goals and customer expectations.
Data minimization not only reduces the risk of data breaches, but it also mandates good data governance and enhances consumer trust. This methodology effectively discourages the unfettered collection and storage of personal data, instead championing an approach to data handling that is both disciplined and driven by specific purposes.
Essentially, data minimization operates under the simple premise that the less data an organization has in its possession, the fewer the opportunities for such data to be misused.
OptIQ Data Security Platform closely follows the requirements of regulatory laws such as GDPR, CPRA, HIPAA, etc to maintain data privacy and protect customer’s data through a stringent process of discovery, classification and governance.
Our platform scans your cloud, on-premise and data lakes to continuously and automatically detect and tag sensitive personal data such as PII, PCI, and PHI. You can even customize your sensitive categories using our data classification engine.
Organization’s data inventory can be viewed and analyzed from a single dashboard, with the capability to govern users using our attribute based access control feature. Our platform is designed to help you understand the context of your data, so as to ease the process of decision making and business analytics. You can maintain all the requirements for data minimization and build a breach-proof strategy for your personal data.
To know more about the capabilities of OptIQ’s Data Security Platform and how we can help you secure privacy and remain compliant, schedule for a personalized demo today.
Minimization in cyber security refers to the practice of collecting, processing, and storing only the minimal amount of data necessary to achieve a specific purpose. This approach reduces the potential attack surface for cybercriminals, lowers the risk of data breaches, and ensures that sensitive information is not unnecessarily exposed. By limiting the amount of data handled, organizations can better protect personal and sensitive information, enhance privacy, and comply with data protection regulations.
Purpose limitation and data minimization are closely related principles in data protection. Purpose limitation requires that data be collected for specific, explicit, and legitimate purposes and not used for other purposes without further consent. Data minimization complements this by ensuring that only the data necessary for those specific purposes is collected and processed. Together, these principles help protect individuals' privacy, reduce the risk of data misuse, and ensure compliance with privacy regulations.
Several data privacy laws explicitly mention data minimization, including:
a. General Data Protection Regulation (GDPR):Article 5(1)(c) of the GDPR states that personal data must be "adequate, relevant, and limited to what is necessary in relation to the purposes for which they are processed."
b. California Consumer Privacy Act (CCPA): While not explicitly named as "data minimization," the CCPA emphasizes the need for businesses to limit the collection and use of personal data to what is necessary and proportionate to achieve the intended purpose.
2. Personal Information Protection and Electronic Documents Act (PIPEDA): PIPEDA requires that organizations only collect, use, and disclose personal information for purposes that a reasonable person would consider appropriate in the circumstances, aligning with the principles of data minimization.
