Here’s a comparison of the top data masking tools on the market, and what you should know when evaluating different vendors.
What are Data Masking Tools?
Data masking tools are software products that anonymize sensitive data, rendering any Personally Identifiable Information (PII) contained in the raw data indetectable. They’re generally considered to be the first line of defense in data protection because, if done right, re-identifying the data would be impossible.
Data masking tools help companies secure data in various industries, such as:
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Financial Services
PCI-DSS, the Payment Card Industry Data Security Standard, is an information security standard created to control cardholder data and reduce credit card fraud.
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Healthcare Services
PHI, Protected Health Information is any health status data, including the provision of, and payment for, healthcare services – that can be linked to a specific individual.
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Commerical Services
PII, Personally Identifiable Information, is any data that can be used to identify someone, including names, addresses, telephone numbers, and Social Security Numbers.
Get Gartner’s market guide for data masking free of charge.
The Need to Comply with Global Data Privacy Laws
Choosing the right data masking tool ensures you stay compliant with the growing range of international data protection regulations, including:
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GDPR
The EU’s General Data Protection Regulation of 2016 spells out the obligations that companies must perform to endow individuals with control and rights over their personal information.
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CPRA
California’s Privacy Rights Act of 2020 extends its Consumer Privacy Act of 2018 specifying data protection obligations for businesses to carry out to provide privacy rights to consumers. Although spearheaded in California, many other US states have since followed suit.
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HIPAA
The US Health Insurance Portability and Accountability Act of 1996 requires healthcare providers to protect sensitive patient health information from being disclosed without the patient’s consent or knowledge.
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SOX
The Sarbanes-Oxley Act of 2002 is a US federal law that requires transparency and accountability in financial record keeping and reporting for corporations.
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DCIA
Canada’s Digital Charter Implementation Act of 2020 provides individuals with control and rights over their personal information as first dictated by Europe’s GDPR.
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APPI
Japan’s Act on the Protection of Personal Information of 2003 regulates the handling of personal information by individuals, government agencies, businesses, and non-profit organizations.
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PDP
Indonesia’s Personal Data Protection Law of 2022 regulates the collection, use, disclosure of personal data by international organizations and governmental and private entities.
What to Look for in a Data Masking Tool
Consider investing in a future-ready data masking tool with full functionality, otherwise you may need to add additional point solutions to fill in the gaps. Make sure the data masking software you choose offers the following features and capabilities:
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Integration with any data source
Many data masking tools are only able to extract data from specific sources. For an enterprise with many different databases, it’s critical that the solution you choose can easily access – and automatically update – data from ALL sources, from legacy mainframe systems and SAP, to MongoDB and NoSQL databases.
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PII Discovery
Data comes in many different formats, which is why it’s important the tool you choose can automatically detect PII scattered all over the enterprise, and can map schema relationships.
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Dynamic data masking
An enterprise-grade data masking tool must be able to dynamically determine who can have access to real data, and to what extent. Dynamic data masking decreases the risk of internal security threats while still enabling individuals and teams to access data when they need it.
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Wide choice of data masking techniques
It’s critical to employ a software that has the ability to work with multiple data masking techniques, like anonymization, pseudonymization, redaction, shuffling, and more. This gives your platform team the flexibility to choose the one that best suits each use case.
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Ability to mask unstructured data
Unstructured data often contains PII, so unstructured data masking is imperative. This can be anything from images and PDFs to XML files and chats. It’s often difficult to detect PII when it’s in unstructured data, but it’s no less important since regulatory bodies do not differentiate between structured and unstructured. Your data masking tool must be able to detect and mask sensitive information in both structured and unstructured formats.
Comparison of the Top Data Masking Tools
Below is a comparison of 6 of the most popular data masking tools, listing the pros and cons for each:
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K2view Data Masking
K2view Data Masking tools are an integral part of its data product platform. The company’s patented data modeling approach organizes data according to individual business entities (such as customers, orders, invoices, or devices). Ideal for enterprises with complex data environments that need to mask data quickly, easily, and at scale, K2view also masks structured and unstructured data in flight, while maintaining referential integrity. Reviewers on peer review sites report that K2view is a powerful tool, but also indicate that it’s a relative newcomer to the market.
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EPI-USE LABS for SAP
EPI-USE LABS specializes in data masking for SAP environments. Its integration with SAP systems ensures data protection within this specific domain. While users say that the tool is simple and transparent, they also indicate that the interface could be clearer – and that they need different tools for their non-SAP databases.
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Oracle Data Masking and Subsetting
Oracle Data Masking and Subsetting tool is a point solution providing data security within Oracle ecosystems. Its integration with Oracle databases simplifies the masking process, but data teams operating in multi-database environments report that the platform is extremely complex, even for expert users – and that their non-Oracle databases require separate solutions.
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IBM InfoSphere Optim Data Privacy
IBM InfoSphere Optim Data Privacy tool offers a data masking solution for companies with complex data environments. Its test data subsetting feature makes it suitable for organizations dealing with diverse data sources. Users complain of functionality gaps, antiquated user interface, and of inadequate data source integration.
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Camouflage Software
Camouflage Software distinguishes itself with its focus on user-friendly interfaces and straightforward implementation. Although it supports various databases and file formats, users with highly specialized or complex requirements may find its feature set somewhat lacking.
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Informatica Cloud Data Masking
Informatica Cloud Data Masking stands out for its versatility and compatibility with a wide range of data sources. Offering comprehensive data masking functionalities, it caters to enterprises with diverse tech stacks. Persistent Data Masking integrates well with Informatica's broader suite, providing a holistic data management approach. However, users commented on a high price tag, steep learning curve, and lack of support.
Choosing Enterprise-Grade Data Masking Technology
In the data masking tools comparison, you need to consider how the solution will scale with your business. According to a recent Gartner report, data masking is becoming increasingly challenging as data environments become more complex. And there’s a definitive need to discover PII automatically across various systems and mask data in any data source, including modern NoSQL databases.
Looking ahead, as a company’s data management needs grow, choosing the right data masking technology now, will certainly pay off down the road.
Learn more about K2view entity-based data masking tools.
