Data Masking 101: How It Works and the Benefits for Businesses

Data Masking 101: How It Works and the Benefits for Businesses

Companies often use data masking when they want to change their records with other company records that are “clean” without revealing the changes.

Whether you’re looking for the right data masking solution, the best practices for implementing it, or just more information about the benefits of data masking, this guide is your one-stop shop for all things data masking.

When you’re marketing a product, service or brand, one of the most important things you’ll need to consider is how to effectively mask data.

 Data Masking

Businesses are always looking for ways to save money. And one way to do that is through data masking. But before we dive into the nitty-gritty of the process, let’s first understand what data masking is.

According to a recent survey by CDP, 81% of small businesses don’t know what data they have been exposed to by third parties and have no idea if they are affected by any data breaches. Data masking can help protect your company from these issues and keep you safe from data theft.

If you’re a data security expert, then you’ve probably heard of Data Masking. In fact, many businesses already have a program in place that is designed to mask their sensitive data. However, not everyone knows how it works or the benefits that this process can have on their business. Learn how to mask your business data with Delphix so that competitors can’t find it. It’s the newest trend in online privacy.

In this post, we’re going to take a look at how data masking can help your business, and how to implement it into your data-driven company.

  1. How Does Data Masking Work?

Here’s how it works: you collect data on a user or their behavior (such as what content they like) through an app, site, or email sign-up form. When a user comes back to that website or app, it will display personalized ads to them based on the data they’ve already provided. This can help you identify things like your target customer’s interests, age, gender, occupation, and other demographic information, which in turn helps you create more relevant marketing campaigns and product development.

Here’s how it works: you collect data on a user or their behavior (such as what content they like) through an app, site, or email sign-up form. When a user comes back to that website or app, it will display personalized ads to them based on the data they’ve already provided. This can help you identify things like your target customer’s interests, age, gender, occupation, and other demographic information, which in turn helps you create more relevant marketing campaigns and product development.

  1. What Are the Benefits for Businesses?

Data masking provides businesses with the ability to hide sensitive or personal information about their users while providing them with more useful and accurate data. The concept behind data masking is simple: users can’t access what they can’t see, so when businesses provide the data, they give users a layer of privacy. It’s also known as anonymization because users are masked from personal information, which means they aren’t able to access it.

One of the biggest benefits businesses can get from data masking is to make the job of data scientists much easier. When we talk about the benefits of data masking in a business context, the first thing to think about is how the organization will leverage the data, the next is the type of data masking, and the last is the time it takes to perform the process.

  1. How Do You Mask Your Data?

There are lots of different ways to mask data—and some are more common than others. Here are a few examples:

Randomized variable names: Instead of giving your data the same name every single time, you might instead use a name like “A” or “B”. This way, you can use different randomizations and make sure that the name is consistent in your data.

Variable name obfuscation: One of the most popular ways to obscure the name of a variable is to use letters (“a”, “b”, etc.) as opposed to numbers. This way, the name is no longer in plain sight and can’t be easily identified by humans, but you still have a consistent pattern to the name of the variable.

Variable re-naming: Another common way to obscure your data is to simply rename the variable. If you have an original data set with a variable called “Height”, you might re-name it to “height” or “height_m”.

Variable renaming and obfuscation: The final, most commonly used method of obscuring data is to name the variable and then create another variable that has a different name.

  1. How Much Does It Cost?

As more companies look to use the power of big data, one question they are often faced with is: How much does masking data cost? The answer, surprisingly, isn’t a lot. Companies using big data can expect to pay anywhere from $10 to $100 per customer and $1,000 to $2,000 in data masking costs.

In conclusion, this is a simple but effective solution for the problem of personal data being stored on corporate computers. And it has huge benefits. By using this technology, companies can save money on their computer hardware, bandwidth, and storage, while improving employee productivity and increasing overall employee satisfaction.

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