Best Data De-Identification Tools for Oracle Database
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Compare the Top Data De-Identification Tools that integrate with Oracle Database as of October 2025
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This a list of Data De-Identification tools that integrate with Oracle Database. Use the filters on the left to add additional filters for products that have integrations with Oracle Database. View the products that work with Oracle Database in the table below.
What are Data De-Identification Tools for Oracle Database?
Data de-identification tools are designed to remove potentially identifiable information from datasets. These tools can be used to ensure that data is anonymized and compliant with data privacy regulations, such as GDPR. Data de-identification methods typically involve techniques like suppressing or masking of certain pieces of data. Other methods like pseudonymization, tokenization, and randomization may also be used in order to completely obfuscate the original data while still allowing analysis of the remaining dataset. Furthermore, some advanced data de-identification software includes additional features for monitoring access and preventing unauthorized use of sensitive personal information. In summary, data de-identification tools provide organizations with ways to ensure compliance by removing personally identifiable information from their datasets before sharing or publishing them publicly. Compare and read user reviews of the best Data De-Identification tools for Oracle Database currently available using the table below. This list is updated regularly.
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Protegrity
Protegrity
Our platform allows businesses to use data—including its application in advanced analytics, machine learning, and AI—to do great things without worrying about putting customers, employees, or intellectual property at risk. The Protegrity Data Protection Platform doesn't just secure data—it simultaneously classifies and discovers data while protecting it. You can't protect what you don't know you have. Our platform first classifies data, allowing users to categorize the type of data that can mostly be in the public domain. With those classifications established, the platform then leverages machine learning algorithms to discover that type of data. Classification and discovery finds the data that needs to be protected. Whether encrypting, tokenizing, or applying privacy methods, the platform secures the data behind the many operational systems that drive the day-to-day functions of business, as well as the analytical systems behind decision-making. -
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Tonic
Tonic
Tonic automatically creates mock data that preserves key characteristics of secure datasets so that developers, data scientists, and salespeople can work conveniently without breaching privacy. Tonic mimics your production data to create de-identified, realistic, and safe data for your test environments. With Tonic, your data is modeled from your production data to help you tell an identical story in your testing environments. Safe, useful data created to mimic your real-world data, at scale. Generate data that looks, acts, and feels just like your production data and safely share it across teams, businesses, and international borders. PII/PHI identification, obfuscation, and transformation. Proactively protect your sensitive data with automatic scanning, alerts, de-identification, and mathematical guarantees of data privacy. Advanced sub setting across diverse database types. Collaboration, compliance, and data workflows — perfectly automated. -
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CipherTrust Tokenization
Thales Cloud Security
CipherTrust Tokenization dramatically reduces the cost and effort required to comply with security policies and regulatory mandates like PCI DSS while also making it simple to protect other sensitive data including personally identifiable information (PII). While there are no tokenization standards in the industry, most tokenization solutions fall into one of two architectures: vaultless- or vaulted tokenization Both secure and anonymize sensitive assets. Tokenization software can reside in the data center, big data environments or the cloud. Tokenization can remove card holder data from PCI DSS scope with minimal cost and effort, enabling organizations to save on costs associated with compliance with the industry standard. Modern IT architectures require both use and protection of personally identifiable information (PII). With CipherTrust tokenization, PII protection is gained without encryption key management required by the software developer.
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