Best Data De-Identification Tools for Hadoop

Unlike most data management systems, PHEMI Health DataLab is built with Privacy-by-Design principles, not as an add-on. This means privacy and data governance are built-in from the ground up, providing you with distinct advantages: Lets analysts work with data without breaching privacy guidelines Includes a comprehensive, extensible library of de-identification algorithms to hide, mask, truncate, group, and anonymize data. Creates dataset-specific or system-wide pseudonyms enabling linking and sharing of data without risking data leakage. Collects audit logs concerning not only what changes were made to the PHEMI system, but also data access patterns. Automatically generates human and machine-readable de- identification reports to meet your enterprise governance risk and compliance guidelines. Rather than a policy per data access point, PHEMI gives you the advantage of one central policy for all access patterns, whether Spark, ODBC, REST, export, and more

Maintain the essence, structure, and accuracy while ensuring confidentiality. Improve data security by anonymizing and altering sensitive information, as well as implementing pseudonymization strategies for adherence to privacy regulations and analytics purposes. The obscured data continues to hold its context and referential integrity, making it suitable for use in testing, analytics, or support scenarios. Serving as an exceptionally scalable and high-performing data masking solution, Informatica Persistent Data Masking protects sensitive information—like credit card details, addresses, and phone numbers—from accidental exposure by generating realistic, anonymized data that can be safely shared both internally and externally. Additionally, this solution minimizes the chances of data breaches in nonproduction settings, enhances the quality of test data, accelerates development processes, and guarantees compliance with various data-privacy laws and guidelines. Ultimately, adopting such robust data masking techniques not only protects sensitive information but also fosters trust and security within organizations.

IBM InfoSphere® Optim™ Data Privacy offers a comprehensive suite of tools designed to effectively mask sensitive information in non-production settings like development, testing, quality assurance, or training. This singular solution employs various transformation methods to replace sensitive data with realistic, fully functional masked alternatives, ensuring the confidentiality of critical information. Techniques for masking include using substrings, arithmetic expressions, generating random or sequential numbers, manipulating dates, and concatenating data elements. The advanced masking capabilities maintain contextually appropriate formats that closely resemble the original data. Users can apply an array of masking techniques on demand to safeguard personally identifiable information and sensitive corporate data within applications, databases, and reports. By utilizing these data masking features, organizations can mitigate the risk of data misuse by obscuring, privatizing, and protecting personal information circulated in non-production environments, thereby enhancing data security and compliance. Ultimately, this solution empowers businesses to navigate privacy challenges while maintaining the integrity of their operational processes.

Your IT department can implement advanced data masking techniques to restrict access to sensitive information, utilizing adaptable masking rules that correspond to the authentication levels of users. By incorporating mechanisms for blocking, auditing, and notifying users, IT staff, and external teams who interact with confidential data, the organization can maintain adherence to its security protocols as well as comply with relevant industry and legal privacy standards. Additionally, you can tailor data-masking strategies to meet varying regulatory or business needs, fostering a secure environment for personal and sensitive information. This approach not only safeguards data but also facilitates offshoring, outsourcing, and cloud-based projects. Furthermore, large datasets can be secured by applying dynamic masking to sensitive information within Hadoop environments, enhancing overall data protection. Such measures bolster the integrity of the organization's data security framework.

Protect, Monitor, and Discover enterprise sensitive data across multiple platforms and environments. Automate your subject rights response and demonstrate regulatory compliance - all in one solution