Table of Contents

    Table of Contents

    Top 5 Data Anonymization Companies in 2023

    Amitai Richman

    Amitai Richman

    Product Marketing Director

    Data anonymization hides or removes PII from datasets to comply with privacy laws. Here’s what look out for when evaluating different vendors and tools. 

    Table of Contents


    How to Choose the Right Data Anonymization CompanyWhat is Data Anonymization?5 Benefits of Using 3rd-Party Data Anonymization ToolsChoosing the Right Data Anonymization Tools
    5 Top Data Anonymization Companies for 2023
    The Best Data Anonymization Companies Take a Business Entity Approach  

    How to Choose the Right Data Anonymization Company  

    In today's data-driven world, organizations collect vast amounts of data. However, the misuse of, or unauthorized access to, this data can pose significant risks. By transforming personal or sensitive data so that it can’t be linked to a specific individual, data anonymization reduces the risk of re-identification and is an essential component of any data protection strategy. Data anonymization tools allow businesses to continue to collect and use data for development, testing, and analytics, while also complying with data privacy laws.  

    With so many companies offering data anonymization services, it can be challenging to identify the most suitable option, especially for enterprises with complex data environments. In this article, we’ll overview why data anonymization matters, and why choosing the right vendor is so important. We’ll also briefly describe the top 5 data anonymization companies you should consider when choosing a partner. 

    What is Data Anonymization? 

    The anonymization of data refers to the act of hiding or removing Personally Identifiable Information (PII) from a dataset to safeguard the privacy of the individuals connected to that data. With anonymized data, it becomes extremely difficult, if not impossible, to identify or link individuals to their specific information. However, the data remains usable for testing, analysis, research, and other legitimate purposes. Data anonymization techniques include data masking, pseudonymization, data aggregation, randomization, generalization, and swapping. 

    5 Benefits of Using 3rd-Party Data Anonymization Tools 

    Partnering with data anonymization companies has its benefits: 

    1. Complying with data privacy regulations 

      Enterprises handle vast amounts of PII from their customers, vendors, employees, and partners. To comply with data privacy regulations such as Europe’s General Data Protection Regulation (GDPR) and the California Privacy Rights Act (CPRA), enterprises need to ensure that sensitive data is properly anonymized and protected. 

    2. Minimizing the risk of data breaches 

      Data breaches can have severe financial and reputational repercussions for enterprises. Through proper data anonymization, the risk of exposing sensitive information during data breaches is dramatically reduced. The right data anonymization tools can help companies protect against unauthorized access. 

    3. Facilitating data sharing and collaboration 

      Organizations often need to share data with external parties, such as business partners or researchers. However, sharing raw data carries significant privacy risks. Data anonymization enables enterprises to share aggregated or de-identified data without revealing sensitive information, fostering collaboration while maintaining privacy. 

    4. Supporting data-driven decision-making 

      Data anonymization allows enterprises to leverage data for analytics, machine learning, and other data-driven initiatives while preserving privacy. By removing personally identifiable elements, companies can perform analysis and extract valuable insights from anonymized data without compromising on privacy. 

    5. Building customer trust 

      In an era where privacy concerns are on the forefront of users’ minds, enterprises need to prioritize customer trust. Enterprises who take data anonymization seriously demonstrate their commitment to protecting customer data and respecting privacy rights, which can, in turn, enhance customer trust, loyalty, and overall brand reputation. 

    Choosing the Right Data Anonymization Tools 

    Identify your top data anonymization questions and clarifications before speaking with vendors. For example, can the tools:  

    • Anonymize data from a variety of structured and unstructured data sources? 
    • Discover the location of sensitive data (PII/PHI) in those data sources? 
    • Pipeline anonymized data from one environment to another? 
    • Transform the data in other ways/formats? 
    • Anonymize the data using out-of-the-box techniques? 

    5 Top Data Anonymization Companies for 2023 

    Here are 5 leading companies to look at when considering a data anonymization partner:  

    1. K2View 

    K2view offers advanced solutions that enable enterprises to securely access, manage, and protect their data. Its entity-based data masking technology helps organizations quickly comply with privacy regulations while preserving data utility. This innovative approach to data anonymization manages and stores all the data for an individual business entity (a specific customer, device, order, etc.) in its own high-performance, compressed, and encrypted Micro-Database™. This represents the highest level of data protection because a mass data breach is impossible. 

    2. IBM InfoSphere Optim Data Privacy 

    IBM InfoSphere Optim Data Privacy provides data masking and anonymization solutions to help organizations protect sensitive information. Their algorithms ensure that personal data is effectively disguised, allowing businesses to share datasets for various purposes without compromising privacy. IBM's longtime experience in data privacy helps organizations mitigate risks associated with unauthorized data access and data breaches. 

    3. Informatica Data Security Cloud 

    Informatica Data Security Cloud is a platform that offers a range of data protection solutions, including data anonymization. By leveraging techniques such as tokenization and data masking, Informatica helps organizations with data de-identification while maintaining its integrity. Their cloud-based approach provides scalability and flexibility, making it easier for businesses to implement data anonymization measures. 

    4. Oracle Data Safe 

    Oracle Data Safe is a cloud-based data security platform that offers a suite of features, including data anonymization capabilities. It enables organizations to mask sensitive information by applying techniques such as encryption, data shuffling, and substitution. Oracle Data Safe provides comprehensive auditing and monitoring tools to ensure data privacy compliance, making it an ideal choice for businesses powered by Oracle data stores. 

    5. Statice 

    Statice is an emerging data anonymization startup that specializes in synthetic data generation. Their innovative technology enables organizations to conduct realistic and privacy-preserving synthetic data generation that retain the statistical properties of original data. By leveraging advanced machine learning algorithms, Statice offers an efficient and secure way to share data while protecting privacy. Their solution helps organizations comply with regulations like GDPR. 

    The Best Data Anonymization Companies Take a Business Entity Approach 

    Data anonymization companies play a critical role in helping organizations effectively navigate privacy regulations and securely share data. When choosing the right data anonymization company to partner with, look for vendors that take a business entity approach. 

    Entity-based data masking is the most effective and advanced way to anonymize data. It manages and stores all the data associated with specific business entities, such as customers, in individually protected Micro-Databases™. With this technology, data teams can securely anonymize data inflight using a variety of techniques, including dynamic data masking, data tokenization, and synthetic data generation.

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