Data Anonymization: 7 Essential Use Cases


Data anonymization is an essential process for sectors ranging from financial, app developers, e-commerce and healthcare.That’s because there are many regulations, such as GDPR, CCPA and HIPAA, that must be carefully followed. And, it can be easy to fall foul of them when there’s sensitive data everywhere.

Simply put, data anonymization is a great way of getting more from your data whilst remaining the right side of legal and ethical lines.

Using the full extent of your data responsibly and legally can be a competitive advantage and is a clear way to reduce compliance costs. That’s because it enables organizations to unlock more value from their data whilst remaining compliant with data regulations. And, with fines running so high (GDPR fines can run up to $22 million), it’s foolhardy for a business to ignore the risks.

Unlocking value in data also often involves sharing it with other parties but without sharing intellectual property or some other sensitive data. Anonymizing data lets you conceal the sensitive parts, lift the restrictions and still benefit from sharing.

This article outlines the ways that people are using data anonymization to:

  • Improve data privacy
  • Gain customer insight
  • Accelerate software development
  • Identify upsell opportunities
  • Improve resource allocation
  • Even reduce crime

So, it’s clear that data anonymization has a lot to offer. Let’s see where the rubber meets the road and look at seven use cases for data anonymization.

What is Data Anonymization?

1. Preserving private information when organizations collaborate

Sharing confidential information is a challenge when organizations work together.

For example, a hospital might need to share patient data with a research lab looking to make medical breakthroughs. But this is out of the question if the data isn’t first made unidentifiable.

With data anonymization, it’s possible to anonymize all data fields that identify an individual (name, age, height, gender, etc.). This means that the valuable data attributes that the research laboratory need are preserved, while the private data attributes are protected.

In the previous case, there’s no need to share data that the third party (the lab) doesn’t need. But, it’s also important to use anonymization so that you can collaborate with another business without sharing business secrets. And, if you do have to share business secrets, you need smart anonymization techniques and an experienced partner to help.

2. Helping retailers glean more insight from customer data

For a retail business to get the most out their customer data, they need specific and well-informed consent from the customers themselves. But businesses often struggle to get this data consent and, therefore fail to leverage useful data for analysis and market research.

However, with data anonymization, it’s possible to remove, hide or cleverly scramble and de-identify personal data. Then, retailers can unlock more value in their data which can lead to better, more actionable business decisions. They can also then share data with third parties to leverage their help.

Indeed, there are many ways data anonymization can help retailers, including:

  • Improving product recommendations
  • Understanding user behavior to personalize ads
  • Creating new product ideas
  • Bettering online services and their user experience

3. Improving fraud detection in the financial sector

In the financial sector, firms are always looking for a better way to decrease risk, and data can help this process.

But, under GDPR, you need customer consent to analyze data. Fortunately, when customer data is sufficiently anonymized, financial firms can get more insight and value from their data.

For example, customer data can be shared and used to improve fraud detection and prevention. This requires large scale anonymization of customer data to develop and train systems so that they can spot suspicious behaviors and transactions.

4. Providing realistic data for software testing

Accelerating the software testing process is key to improving the value delivery of software projects.

To test apps effectively, third party developers need ‘realistic’ test data. That’s because realistic data enables you to weed out the real problems and not miss anything out.

Automated tools can test the software, but, ultimately, you need real user behavior baked into real data. Once again, GDPR typically prevents this data from being usable. But, when you anonymize the data, this real data is safe to process.

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5. Longer data retention for improved business analysis

Strict data regulations dictate how long you can keep data. But, with anonymized data, the rules on the retention period cease to apply.

So now, you can analyze your business performance or customer behavior over long periods of time without running the risk of violating your license to use the data.

6. Policing and data publishing in the public sector

So far, we’ve mostly addressed how the private sector can utilize data anonymization, but it can also help public sector bodies, too.

An example of this is software which is used to makes crime predictions using anonymized data. It does this by looking at crime records and data from social networks. This has led to an 8-9 percent reduction in crime in certain areas.

There is also a big need for anonymization in various public sector initiatives, for example, Open Data initiatives and National Statistics offices need to publish lots of data which needs to be carefully curated/de-identified.

7. Automotive innovation via car driver behavior analysis

The automotive industry also uses data anonymization.

For example, Tesla collect driver behavior data from their cars, including the cars performance, location, speed etc. They then anonymize this data to protect the privacy of their drivers.

Also, modern cars have lots of cameras, and these cameras see people, license plates etc. And so, there’s a whole industry dedicated to anonymizing this data so that you can feel safe around modern cars on the street. This goes much further than just blurred faces on Street View.

These are just a few ways that anonymization and big data are changing the automotive industry.

Data anonymization done the smart way

No matter your industry, there are plenty of opportunities to unlock more value from your data by using data anonymization.

Sometimes, it’s simply removing parts of the data that you don’t need for your specific use.

But other times, it’s more difficult. For example, when you need to keep the personal data. Then, you must cleverly change, mix, and obfuscate the data in a way that makes it extremely hard or impossible to recreate the sensitive part.

That’s where CloverDX can help.

We use our own anonymization framework to find sensitive data, classify it and anonymize it for a specific use. And, our enterprise anonymization can tackle projects at any scale – even thousands of database tables, and dozens or hundreds of systems.

From here, you can draw the insights and value you need to make informed business decisions while keeping the right side of regulations and ethical lines.

To learn more about data anonymization and the CloverDX approach, watch our webinar below.

Removing danger from data - webinar - watch now


Posted on December 05, 2019
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