Data masking is an effective business tool used by large companies around the world to save time and money while improving their strategies.

The following three principles are: save time, save money and save resources. Saving time means spending only what is necessary. Saving money means not spending more than necessary. And saving resources means not wasting things that can be used over and over again. To do this, data masking allows us to see precisely what we have and don't have, so we can be intentional about how we spend it.

Companies obfuscate their data, such as names, numbers, and specific details, before publishing them in public forums such as blogs and social networks. Once you have masked your data, you can make adjustments without worrying about making mistakes that could lead to negative comments or lawsuits. Companies use this tactic to protect their brand, improve customer relationships and increase sales.

• Data is personal. They define who you are, where you have been, and what you are capable of.


• Data is valuable. They are the key to being able to learn and make better decisions.


• Data is power. It is the key to helping people reach their full potential.


• Data must be anonymous. Data-driven decision-making is essential, but it cannot be used to violate people's privacy.


• Data must be clean. The information we collect must be unbiased, reliable, and not misleading.


• The data must be secure. It must be protected against unauthorized access.

Database protection techniques and strategies

To ensure adequate protection of an organization's databases, a defensive Best Practices Matrix is needed, along with regular internal controls. The Best Practices Matrix includes the following elements:

• Manage user access rights and eliminate excessive privileges and inactive users.


• Train employees in risk mitigation techniques, including recognition of common cyber threats such as targeted phishing attacks, best practices for Internet and email use, and password management.


• Assess database vulnerabilities, identify compromised endpoints and classify sensitive data.


• Monitor all database access activity and usage patterns in real-time to detect data leaks, unauthorized SQL and big data transactions, and protocol/system attacks.


• Automate auditing with a database auditing and protection platform.


• Block malicious web requests.


• Archive external data, encrypt databases and mask database fields to hide sensitive information.

In conclusion, this is why it is important to use data masking in your projects and not just for data security purposes. Data masking is a powerful tool that allows you to see exactly what your data looks like in your database and can also help you make sure there are no errors. It will show you all the fields that have been created, including column names and column types, which can help you see problems and potential problems with your data in case of errors. You can also use it to test a small subset of your data, to get an idea of the total size of your table and how many rows it contains. This will help you plan your next steps.