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How to Secure Your Critical Sensitive Data in Non-Production and Testing Environments

For organizations that depend on high-quality data for their software development processes but also want to ensure that any sensitive information contained within it is not exposed, a good static data masking tool is a crucial requirement for business operations.

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How to Secure Your Critical Sensitive Data in Non-Production and Testing Environments

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  1. How to Secure Your Critical Sensitive Data in Non-Production and Testing Environments www.magedata.ai

  2. Digital Transformation: The New Challenge For Business Data security is becoming increasingly complex as different departments within an organization use data in different ways to support their objectives. Static data masking is a key requirement for protecting sensitive data from being exposed in non-production and testing environments. A good static data masking tool can protect data from being seen or altered by unauthorized users. www.magedata.ai

  3. Protect data in non-production environments To protect data in non-production environments, it is important to understand the different security requirements. De-identifying or masking the data is recommended as a best practice for protecting sensitive data involved. Masking techniques secure both structured and unstructured fields in the data landscape. Masking techniques can be used to protect both user-based access and quality assurance requirements of the data. www.magedata.ai

  4. Maintain integrity of secured data Data security and usability are both important when it comes to securing data. Static data masking tools can help to keep the data usable while still providing a level of security. These tools can be useful for a variety of purposes, including business analytics, application development, testing, training, and more. www.magedata.ai

  5. Choice of anonymization methods Organizations will have multiple anonymization use cases, based on the security and performance needs of the relevant teams. Some anonymization methods can be more valuable than others, depending on the needs of the specific team. Good tools offer different anonymization methods that can be used efficiently to protect sensitive data. Mage has created a range of security measures to protect non-production data, including data masking tools for securing that data in non-production environments www.magedata.ai

  6. Thank You Contact Us CORPORATE HEADQUARTERS 3 Columbus Circle, 15th Floor New York, NY 10019 Email: info@magedata.ai Phone: +1 212 203 4365 www.magedata.ai

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