Data masking tackles security issues head-on by tweaking data's actual digits and letters, maintaining confidentiality. It alters data values while preserving the original format, creating a pseudo-version for testing, research, or training. Developers use data masking to curb security risks during the development and testing phases. Some companies leverage masked data for employee onboarding, allowing skill practice without exposing critical assets.

What are the benefits of data masking?

It aids companies in adhering to data privacy regulations and compliance standards, acting as a robust defense against threats like data loss and breaches. Cost-effective compared to pricier encrypted solutions, masked data retains the functional properties of the original without revealing its true value.

There are different ways and challenges in masking data. Check out the top 5 best data masking software in 2023 outlined below to create realistic and structurally similar datasets: 

1 DATPROF Test Data Management Platform

(Photo: DATPROF)

Overview

DATPROF simplifies the test data acquisition process, allowing software development teams to prioritize delivering top-notch software. With a 20-year track record, the company excels in streamlining test data for medium to large organizations globally. Many have benefited from the Test Data Management Platform, enabling developers and testers to innovate swiftly and construct high-quality products.

DATPROF's toolset offers solutions to identify sensitive data, create anonymized data subsets, virtualize containerized databases, generate synthetic test data, and automate test data deployment. The Test Data Management Platform's speed, user-friendliness, and data integrity empower organizations to optimize their software development cycles.

The data masking software seamlessly supports all major relational databases, facilitating efficient test data management to overcome various test data challenges.

Many organizations, spanning diverse industries, require data for application development and quality testing. However, using real-world datasets poses the risk of exposing personal or sensitive information. DATPROF's Test Data Management Platform enables anonymization of data  through data masking and synthetic data generation, ensuring the necessary test data for execution.

Features

Test data management involves data masking to create and provide realistic test data for different use cases like QA, development, testing, and training. The data masking software of DATPROF can protect privacy-sensitive data by anonymizing it through data obfuscation or synthetic data generation. Outlined below are its main features: 

Data Masking Techniques

Data masking involves reusing or modifying data in databases. DATPROF masks by implementing the following techniques:

• Shuffle: This involves taking the distinct values of one or multiple columns and rearranging them to create new name combinations of data. 

• Scramble: This replaces characters by x and numbers by 9 to make the data unrecognizable. 

• Random Lookup: This technique uses a reference table to replace values by randomly selecting data from another table. 

• Custom Expression: Users can leverage the flexibility of custom expressions instead of standard functions to alter the composition of real datasets. 

• Blank: This technique removes a column from a table to hide the dataset. This is only recommended for columns not used in testing.  

• First Day in Month/Year: This alters the date of birth to the first month or year, making it harder to trace the data to a specific person. 

• Value Lookup: This technique uses a reference table to anonymize the values of the data. It requires a reference key to locate the original data. 

Synthetic Test Data Generation

In cases where data masking techniques fall short, DATPROF employs 50+ built-in generators to produce synthetic test data. This artificial data replaces privacy-sensitive information in a testing environment, ensuring compliance with data protection regulations and meeting specific testing requirements.

Multi-database Masking

DATPROF achieves consistent data masking across multiple tables through deterministic data masking. It ensures uniform data masking, replacing values consistently across all sources and applications, whether within the same row, table, schema, or between instances, servers, and database types. It can replace a value in a column with the same value, like modifying every dataset containing "Lynne" into "Denise". 

DATPROF understands the importance of data masking to protect privacy-sensitive data and maintain compliance with privacy laws. Leverage its data masking software to have better data protection and produce test data for different teams.

Video to embed: DATPROF - Test Data Simplified

2 Mage Platform

(Photo: Screenshot from Mage website)

Overview

Mage takes care of the data privacy and security needs of enterprises so they can focus on growing their business. It is an industry-leading solution, recognized by Gartner Peer Insights as the Customers' Choice for three consecutive years. It has also received its ISO/IEC 27001, proving it abides by the international standard for information security management systems.  

Features

Static Data Masking

Static data masking replaces sensitive data with fake but realistic data. Mage offers more than 60 different anonymization methods so enterprises can secure their data effectively. These methods balance protection and performance, promising consistent results across applications and data stores so businesses can maintain referential integrity for maximum usability. 

The Mage platform also features a variety of NIST-approved encryption and tokenization algorithms, which safeguard the sensitive value of data. Encryption supports structured and unstructured fields and even databases that aren't stored in multiple systems. Enterprises can use this method of anonymization to protect files and data that are exchanged with third parties. 

On the other hand, tokenization replaces the data with a random string of values (or tokens) instead of being modified by an algorithm. It preserves the format of the data, maintaining high security and usability. 

Enterprises can also minimize the risk of re-identification by using the Mage Identities masking method. They can also generate a fake dataset using logic and AI without losing the attributes of the original data. The AI, together with natural language processing, can understand the context and discover sensitive data in unstructured fields or sensitive data deeply hidden in log files.

Dynamic Data Masking

Dynamic data masking of Mage provides 40+ anonymization methods, so enterprises have the flexibility to take control of sensitive data in production and non-production environments. They can mask sensitive data at application and database layers with customizable solutions.

The platform features rules within the product UI, which users can configure to activate role-based, user-based, program-based, and location-based access controls. These restrict or grant access to sensitive data. These authorization rules benefit companies with offshore offices, given they can control who can view the sensitive data based on a data classification-centric anonymization technique. Guaranteed the data remains secure in transit, at rest, or in use. 

Mage also offers blended and hybrid data masking to address unique cases like cloud migration. Enterprises can leverage both to maintain the integrity of application clusters while migrating individual applications to the cloud without hassle. Their data remains secure both in the database and application layer.  

3 Informatica Cloud Data Masking

(Photo: Screenshot from Informatica website)

Overview

85 Fortune 100 companies use Informatica and deal with 71 trillion cloud transactions monthly. It helps them meet compliance goals through its Cloud Data Masking. It creates safe and more secure data, which customers can use in testing, development, data analytics, supply chains, customer experience programs, and more. 

The data masking software of Informatica anonymizes sensitive information that can potentially compromise the privacy, security, or compliance of business data. It also provides scalability, management, and connectivity ranging from a variety of databases. 

Businesses can rely on the consistent data masking policies of Informatica. It provides a single audit trail so anyone can track the procedures made for protecting sensitive data by accessing the audit logs and reports of the software. It simulates the rules before they are implemented so users can validate the policies, define and reuse the rules that comply with said policies, and produce quick results with instream masking.

Features

Single, Scalable Data Masking Environment

Informatica features a single, scalable data masking environment where users can create and centrally manage masking processes. It can handle large volumes of data, ensuring high performance and enterprise-level connectivity.

Robust Data Masking Support

It also features structural rules that de-identify values through substitution, blurring, randomization, and other methods of masking. It also contains built-in masking techniques designed to anonymize credit card numbers, SSNs, phone numbers, financial data, and more. 

Broad Connectivity & Application Support

Informatica offers broad connectivity and application support so users can access and mask various databases, mainframes, and business applications such as Oracle and Microsoft SQL Server. Anyone can apply the masking algorithms to any personal or sensitive data, depending on the format. The masking rules and standards created are also automatically implemented across enterprise systems to maintain data consistency.

The native capabilities of Informatica Cloud Data Masking simplify the maintenance and administration of data governance, privacy, and compliance. It can improve the security assurance of test and analytics environments without ruining the quality of the test data used for development, testing, and training. Businesses can leverage the software to uphold data privacy and expand data security across enterprise systems.

4 Satori

(Photo: Screenshot from Satori website)

Overview

Satori is a data security platform for security and engineering teams with dynamic data masking abilities. It anonymizes data according to security policies, users, roles, and datasets. It is simple to use, unlike other solutions advertised to streamline security controls. It does not require any additional code or any changes to data storage (databases, data warehouses, or data lakes). 

Features

Universal Masking

It is common practice for companies to store data across different platforms. While this increases the safety of critical assets, it also complicates the data masking procedure and increases the cost of maintenance in the long run. Satori can dynamically mask all sensitive data across multiple data stores. Users don't need to input any additional code despite the different native capabilities of data stores or BI tools.

Reusable Dynamic Masking Profiles

Businesses can reuse the same dynamic masking policies, streamlining the data masking process to reduce error and generate proxy data quickly across platforms. 

Zero Configurations

Satori can also mask semi-structured data without needing any specific configurations. Typically, it requires more detail which results in complex and convoluted policies and conditions, delaying the process. The data security platform simplifies dynamic data masking with zero configurations. Regardless of the data location and data type, it masks using the same policies used for structured data.

Businesses can quickly meet security and compliance requirements by leveraging the dynamic data masking ability of Satori. It also contains features for data classification, posture management, access control, and more so anyone can protect sensitive data in the cloud. Security and engineering teams can monitor everything in one place as it provides visibility on all data stores and enforces policies without making configurations.

5 K2view

(Photo: Screenshot from K2view website)

Overview

K2view is a data product platform that can rapidly generate data products so teams can organize and deliver data efficiently. It offers real-time responsiveness, powering data operations at 200 msec speed, and supports all data sources. 

Features

K2view features over a hundred built-in data masking functions. Anyone can customize and reuse them to streamline the process across different data storages. Admins can set up role-based and attribute-based access controls to restrict or permit access so that only authorized users can access sensitive data and prevent data breaches. 

It can also mask unstructured files such as images, PDFs, or text files. Users can even generate synthetic, digital versions of personal assets like receipts, checks, and contracts. The data product platform can seamlessly integrate with any data source, technology, or vendor. Businesses can deploy the platform on-premise or in the cloud. 

K2view ingests data from multiple sources and automatically organizes it by business entities. This enforces referential integrity and facilitates contextual masking, helping data teams have better data management. It masks the organized data in the context of the business entity and delivers it to the data store while still preserving its integrity.

Businesses can leverage the data masking software to drive productivity as K2view already contains prebuilt masking functions and requires no code configuration. It integrates data masking into the CI/CD pipelines, accelerating the process for the generation of proxy data. It is scalable and future-proof, thus lowering the costs spent on per-database fees.

Conclusion

Data masking provides a functional substitute so organizations can maintain compliance in using data for tests, training, and other applications. It grants access to information without compromising the privacy of customers and organizations. Choose from the top 5 data masking software to achieve better data protection.