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More isn’t always better.

In today’s digital landscape, we have access to more data than ever before. Approximately 2.5 quintillion bytes worth of data are generated each day, with over 44 zettabytes of data currently in the world.

But is this abundance of data creating risks for companies? The answer is a resounding yes.  Processing and storing too much data presents major challenges, from compliance with data privacy regulations to increasingly sophisticated cyberattacks, across industries.

One strategy to safeguard sensitive information is data minimization. Today, we’ll delve into the intricacies of data minimization, its significance to data privacy and compliance, and several top strategies for implementing it.

What is data minimization?

Data minimization is a core concept for many data privacy regulations, including the 

California Consumer Privacy Act (CCPA) and the EU’s General Data Protection Regulation (GDPR). In a nutshell, it’s a proactive approach to data security that revolves around the principle of collecting, storing, and processing as little personal or sensitive data as possible. 

Data minimization stands in direct contrast to the more conventional big-data mentality wherein “data is king.” That mindset leads organizations to amass large volumes of data and consequently increase the risk of data exposure and misuse.

As defined by the European Data Protection Supervisor (EDPS), the independent supervisory authority that monitors data privacy for European institutions, data minimization means that data controllers must limit the collection and retention of personal information to only what is directly necessary to accomplish a specified purpose. “In other words,” the EDPS notes, “data controllers should collect only the personal data they really need, and should keep it only for as long as they need it.” 

The principle of data minimization forms Article 5(1)(c) of the GDPR, and data purpose limitation is increasingly appearing in data privacy frameworks. But data minimization is also framed by privacy scholars as a human rights issue, since “data that is not collected cannot harm people.” Privacy advocates note that reducing the amount of personal data collected is important both to respect people’s wishes and to prevent that data from being misused in harmful ways.

What are the benefits of data minimization?

If your organization has been operating under the assumption that more data is better, data minimization might be a stark change. However, it can pay off in greater data security, lower costs, and other benefits.

The strategy can be successful even at the enterprise level. As Forbes notes, even Walmart relies on only four weeks of data at a time to set day-to-day merchandising strategies.

Meeting compliance. The most obvious benefit of data minimization is meeting compliance with data protection regulations such as the GDPR and CCPA, which emphasize data minimization as a foundational practice. These regulations rightly recognize that the less data organizations have, the easier it is for consumers and citizens to protect their sensitive information.

Reduced attack surface. Data minimization is also key for healthy cybersecurity practices. By collecting and retaining only essential data, organizations can significantly reduce their attack surface. In the event of a breach, phishing attack, or insider threat, having minimal data on hand will limit potential damage and shrink the scope of the breach.

Reduced data storage costs. Talk of “cloudflation” over the past year has led many organizations to reduce their data storage budgets and seek out cloud optimization strategies. One of the simplest ways to shrink storage costs, of course, is keeping only the data that’s absolutely relevant and necessary.

Improved AI models. It’s common knowledge that AI technologies depend on large datasets, so it might seem counterintuitive to suggest that data minimization could improve AI models. However, AI and ML technologies depend heavily on data processing, which is more effective when data is collected and stored with clear purpose and reliable labeling. (Think of it as the difference between building a model airplane in a well organized workshop versus in a garage full of junk.)

Enhanced company reputation. Fostering a data minimization approach may even enhance an organization’s reputation as a responsible custodian of sensitive data. Consumers and B2B customers alike are increasingly worried about data privacy, and having a clear data minimization policy in place can help allay concerns and foster trust.

What isn’t data minimization?

With so many clear benefits to data minimization, it’s easy to get caught up in simply deleting data indiscriminately. But data minimization goes beyond just having less data. Rather, it requires a nuanced approach that balances the need for information with the need to protect it.

Data minimization is not just reducing data collection. The spirit of data minimization isn’t just about collecting less data. It’s also about setting limits on data processing activities. Sensibly restricting what an organization can do with sensitive data — and who is granted access to that data — once it’s been collected is key.

Data minimization is not setting blanket deletion policies. Data minimization isn't synonymous with blanket data deletion. Unless a company reviews its data practices carefully and establishes nuanced policies, it might reduce the overall amount of data it collects, processes, or stores — without ever reducing its security and compliance risks. On the other hand, arbitrary data deletion might inadvertently remove critical material that offers valuable insights. Understanding which data is sensitive but unnecessary, versus which data is necessary to achieve business objectives (and therefore necessary to protect), is key.

How should organizations implement data minimization?

Implementing data minimization requires a well-structured and comprehensive approach. Data minimization policies should align with an organization’s goals, legal responsibilities, and industry standards — while also protecting individual data privacy rights. Here are a handful of strategies to consider:

Perform a data audit. Most organizations don’t know where all their data resides or what information it comprises. A good starting point is to perform a thorough audit of all personal data collected, processed, and stored within the organization. After creating an inventory that includes types of data, sources of data, and purposes of data collection, companies can better understand their data landscape and make more informed decisions. From there, they can identify and keep only what is truly necessary to achieve their core objectives.

Limit data access and sharing. In large organizations, data may be accessed by and shared among several different internal teams as well as third-party vendors. Enterprises should make sure that data is only shared when necessary and that their security controls include the principle of least privilege. To prevent data leaks and exposure, teams should also employ a policy of working with the absolute minimum amount of data needed to achieve their objectives.

Erase, erase, erase. Businesses should establish policies and schedules for deleting outdated and unnecessary data. Good data governance processes will include regularly reviewing and eliminating data that no longer serves a purpose — while also examining broader data retention patterns at the organizational level.

Regularly review consent processes. Receiving informed consent for data collection and processing is an important element of not just data minimization but also compliance with data privacy regulations. Companies should ensure that their consent mechanisms are clear, transparent, and specific.

Employee training. Finally, businesses must train employees and stakeholders about the principles and practices of data minimization. Ensure that everyone handling data understands the importance of collecting only necessary data and the consequences of potential data breaches.

When data can’t be minimized

Even with the most comprehensive data minimization plan, most organizations will still need to collect, store, and process a certain amount of sensitive data. To protect this data against loss, theft, exposure, and unauthorized access, companies must implement robust data privacy and security measures.

One option is to protect sensitive data with the ShardSecure platform. Our technology offers an innovative approach to file-level encryption that separates data from infrastructure owner and admin access, ensuring advanced privacy from third parties. Even if a storage location is breached, sensitive data will remain unintelligible and unexploitable to unauthorized users.

Ensuring data protection through frameworks like privacy by design and data minimization are not only essential to protect individual rights; they’re also increasingly important to gain trust for B2B customers. To learn more about strengthening your data privacy and protection measures with ShardSecure, get in touch with us today.


30+ Incredible Big Data Statistics (2023) | Exploding Topics

Data Minimization: Limiting the Scope of Permissible Data Uses to Protect Consumers | Epic

Glossary: D | European Data Protection Supervisor

Three Years Under the EU GDPR | Access Now

Why Data Minimization Is an Important Concept in the Age of Big Data | Forbes

Why Your Cloud Expenses Are Rising: Blame Cloud-flation | Transforming Data with Intelligence

Adopting a Smart Data Mindset in a World of Big Data | McKinsey

Why Data Minimization is a Key Principle of Data Privacy | K2View

What Role Can Internal Auditors Play in GDPR Compliance? | The International Association of Privacy Professionals

The Art of Letting Go: How Data Minimization Can Improve Cybersecurity and Reduce Cost | Forbes