# Best Data Masking Software for Medium-Sized Businesses *By [Lauren Worth](https://research.g2.com/insights/author/lauren-worth)* Products classified in the overall Data Masking category are similar in many regards and help companies of all sizes solve their business problems. However, medium-sized business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Medium-Sized Business Data Masking to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Medium-Sized Business Data Masking category. In addition to qualifying for inclusion in the Data Masking Software category, to qualify for inclusion in the Medium-Sized Business Data Masking Software category, a product must have at least 10 reviews left by a reviewer from a medium-sized business. ## Category Overview **Total Products under this Category:** 92 ## Trust & Credibility Stats **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 4,800+ Authentic Reviews - 92+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. ## Top-Rated Products (Ranked by G2 Score) ### 1. [Agentforce 360 Platform (formerly Salesforce Platform)](https://www.g2.com/products/agentforce-360-platform-formerly-salesforce-platform/reviews) Salesforce Platform is the leading low-code development platform that empowers your team to build and extend your Customer 360 with AI, automation, and data. With the Salesforce Platform, you can execute on your Customer 360 vision, securely, and keep your customer at the center of everything you do. Access a harmonized, unified view of your customers, automate manual, inefficient processes to drive productivity, and empower your employees to deliver a seamless, connected customer experience. Accelerate your Salesforce development, increase developer efficiency, and save on IT costs with the Salesforce platform. **Average Rating:** 4.5/5.0 **Total Reviews:** 3,767 **User Satisfaction Scores:** - **Ease of Admin:** 8.5/10 (Category avg: 8.6/10) - **Static Masking:** 9.1/10 (Category avg: 8.5/10) - **Dynamic Masking:** 9.2/10 (Category avg: 8.4/10) - **Sensitive Fields:** 9.5/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Salesforce](https://www.g2.com/sellers/salesforce) - **Company Website:** https://www.salesforce.com/ - **Year Founded:** 1999 - **HQ Location:** San Francisco, CA - **Twitter:** @salesforce (581,281 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3185/ (88,363 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Salesforce Developer, Account Executive - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 45% Mid-Market, 34% Enterprise #### Pros & Cons **Pros:** - Ease of Use (1639 reviews) - Features (799 reviews) - Customization (674 reviews) - Customizability (670 reviews) - Customization Options (630 reviews) **Cons:** - Learning Curve (574 reviews) - Complexity (539 reviews) - Expensive (485 reviews) - Difficult Learning (413 reviews) - Missing Features (412 reviews) ### 2. [Oracle Data Safe](https://www.g2.com/products/oracle-data-safe/reviews) Data Safe is a unified control center for your Oracle Databases which helps you understand the sensitivity of your data, evaluate risks to data, mask sensitive data, implement and monitor security controls, assess user security, monitor user activity, and address data security compliance requirements. Whether you’re using Oracle Autonomous Database or Oracle Database Cloud Service (Exadata, Virtual Machine, or Bare Metal), Data Safe delivers essential data security capabilities as a service on Oracle Cloud Infrastructure. **Average Rating:** 4.3/5.0 **Total Reviews:** 62 **User Satisfaction Scores:** - **Ease of Admin:** 8.1/10 (Category avg: 8.6/10) - **Static Masking:** 8.5/10 (Category avg: 8.5/10) - **Dynamic Masking:** 8.6/10 (Category avg: 8.4/10) - **Sensitive Fields:** 9.1/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Oracle](https://www.g2.com/sellers/oracle) - **Year Founded:** 1977 - **HQ Location:** Austin, TX - **Twitter:** @Oracle (827,310 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1028/ (199,301 employees on LinkedIn®) - **Ownership:** NYSE:ORCL **Reviewer Demographics:** - **Who Uses This:** Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 45% Enterprise, 29% Small-Business ### 3. [Satori Data Security Platform](https://www.g2.com/products/satori-data-security-platform/reviews) Satori is a Data Security Platform (DSP) that enables self-service data and analytics. Unlike the traditional manual data access process, with Satori, users have a personal data portal where they can see all available datasets and gain immediate access to them. Satori’s DSP dynamically applies the appropriate security and access policies, and the users get secure data access in seconds instead of weeks. Satori’s comprehensive DSP manages access, permissions, security, and compliance policies - all from a single console. Satori continuously discovers sensitive data across data stores and dynamically tracks data usage while applying relevant security policies. Satori enables data teams to scale effective data usage across the organization while meeting all data security and compliance requirements. **Average Rating:** 4.7/5.0 **Total Reviews:** 87 **User Satisfaction Scores:** - **Ease of Admin:** 8.8/10 (Category avg: 8.6/10) - **Static Masking:** 9.4/10 (Category avg: 8.5/10) - **Dynamic Masking:** 9.0/10 (Category avg: 8.4/10) - **Sensitive Fields:** 9.3/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Commvault](https://www.g2.com/sellers/commvault) - **Company Website:** https://www.commvault.com - **Year Founded:** 1996 - **HQ Location:** Eatontown, New Jersey, United States - **Twitter:** @Commvault (64,790 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/163166/ (3,456 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Software Engineer - **Top Industries:** Computer Software, Computer & Network Security - **Company Size:** 56% Mid-Market, 24% Enterprise #### Pros & Cons **Pros:** - Ease of Use (16 reviews) - Security (14 reviews) - Access Control (13 reviews) - Data Protection (11 reviews) - Features (11 reviews) **Cons:** - Complexity (7 reviews) - Complexity Management (5 reviews) - Slow Performance (5 reviews) - Expensive (4 reviews) - Improvement Needed (4 reviews) ### 4. [VGS Platform](https://www.g2.com/products/very-good-security-vgs-platform/reviews) Very Good Security (“VGS”) makes it easy for customers to collect, protect and share sensitive financial data in a way that accelerates revenue, eliminates risk, ensures compliance, and drives profitability. VGS secures that information in an encrypted token vault; enabling our customers to de-risk their technical environment and achieve compliance certifications like PCI DSS, SOC 2, GDPR, and more, faster. VGS delivers a modern solution to collect, protect, and exchange sensitive data that spans from data privacy to payment acceptance and card issuance; providing businesses with tokenization, PCI compliance, data security, processor optionality, and the ability to operate on that data without compromising their security posture. VGS delivers a modern payments security solution that gives businesses ownership and control over critically valuable customer data, granting them maximum portability, operationality, and value extraction. VGS customers decouple the value and utility of data from the associated security and compliance risks and allow customers to achieve continuous PCI DSS compliance 16x faster, at 25% the cost of a DIY approach. **Average Rating:** 4.7/5.0 **Total Reviews:** 46 **User Satisfaction Scores:** - **Ease of Admin:** 9.3/10 (Category avg: 8.6/10) - **Static Masking:** 9.5/10 (Category avg: 8.5/10) - **Dynamic Masking:** 9.5/10 (Category avg: 8.4/10) - **Sensitive Fields:** 9.4/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Very Good Security](https://www.g2.com/sellers/very-good-security) - **Year Founded:** 2015 - **HQ Location:** San Francisco, California - **Twitter:** @getvgs (1,430 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/18142614/ (452 employees on LinkedIn®) **Reviewer Demographics:** - **Who Uses This:** Software Engineer - **Top Industries:** Financial Services, Banking - **Company Size:** 51% Mid-Market, 45% Small-Business ### 5. [Tonic.ai](https://www.g2.com/products/tonic-ai/reviews) Tonic.ai frees developers to build with safe, high-fidelity synthetic data to accelerate software and AI innovation while protecting data privacy. Through industry-leading solutions for data synthesis, de-identification, and subsetting, our products enable on-demand access to realistic structured, semi-structured, and unstructured data for software development, testing, and AI model training. The product suite includes: - Tonic Fabricate for AI-powered synthetic data from scratch - Tonic Structural for modern test data management - Tonic Textual for unstructured data redaction and synthesis. Unblock innovation, eliminate collisions in testing, accelerate your engineering velocity, and ship better products, all while safeguarding data privacy. Founded in 2018, with offices in San Francisco, Atlanta, New York, and London, the company is pioneering enterprise tools for data synthesis and de-identification in pursuit of its mission to unblock innovation with usable data. Thousands of developers use data generated with the Tonic.ai platform on a daily basis to build products and train models faster in industries as wide ranging as healthcare, financial services, insurance, logistics, edtech, and e-commerce. Working with customers like Comcast, eBay, UnitedHealthcare, and Fidelity Investments, Tonic.ai builds developer solutions to advance its goals of advocating for the privacy of individuals while enabling companies to do their best work. Be free to build with high-fidelity synthetic data for software and AI development. **Average Rating:** 4.2/5.0 **Total Reviews:** 38 **User Satisfaction Scores:** - **Ease of Admin:** 8.3/10 (Category avg: 8.6/10) - **Static Masking:** 8.7/10 (Category avg: 8.5/10) - **Dynamic Masking:** 7.6/10 (Category avg: 8.4/10) - **Sensitive Fields:** 8.7/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Tonic.ai](https://www.g2.com/sellers/tonic-ai) - **Company Website:** https://www.tonic.ai/ - **Year Founded:** 2018 - **HQ Location:** San Francisco, California - **Twitter:** @tonicfakedata (699 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/18621512 (100 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Computer Software, Financial Services - **Company Size:** 45% Mid-Market, 32% Small-Business ### 6. [Informatica Data Security Cloud](https://www.g2.com/products/informatica-data-security-cloud/reviews) Informatica Data Security Cloud is a comprehensive solution designed to protect sensitive and private data, enhance compliance, and enforce data usage policies without requiring changes to existing applications. By leveraging advanced data masking and anonymization techniques, it ensures that critical information remains secure across various environments, including testing, development, analytics, and customer experience programs. This cloud-native service integrates seamlessly with Informatica's Intelligent Data Management Cloud, providing a holistic approach to data governance and privacy. Key Features and Functionality: - Cloud Data Masking: De-identifies and anonymizes sensitive data to prevent unauthorized access, supporting compliance and data security initiatives. - High-Performance Data Masking: Centrally manages and scales masking processes for large data volumes across diverse data stores and locations. - Robust Data Masking and Encryption: Utilizes various techniques such as substitution, format-preserving encryption (FPE, blurring, sequential, and randomization to protect data. - Broad Connectivity and Custom Application Support: Supports data masking across multiple formats and a wide range of databases, mainframes, and applications. - Automated Data Discovery: Identifies sensitive data locations quickly, ensuring consistent masking across databases. - Self-Service Data Warehouse: Stores, augments, shares, and reuses test datasets to improve testers’ efficiency. - Data Subset: Provisions smaller datasets to minimize infrastructure requirements and enhance performance. - Monitoring and Reporting: Engages risk, compliance, and audit teams to align with data governance initiatives. Primary Value and User Solutions: Informatica Data Security Cloud addresses the critical need for organizations to protect sensitive data while maintaining operational efficiency. By anonymizing and de-sensitizing data, it reduces the risk of data breaches and ensures compliance with data privacy regulations. The solution's ability to manage and scale data masking processes across various environments allows businesses to securely utilize data in testing, development, analytics, and customer experience initiatives without compromising data integrity or security. This empowers organizations to confidently share and use data, fostering innovation and informed decision-making. **Average Rating:** 4.0/5.0 **Total Reviews:** 45 **User Satisfaction Scores:** - **Ease of Admin:** 7.8/10 (Category avg: 8.6/10) - **Static Masking:** 7.9/10 (Category avg: 8.5/10) - **Dynamic Masking:** 8.4/10 (Category avg: 8.4/10) - **Sensitive Fields:** 8.9/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Informatica](https://www.g2.com/sellers/informatica) - **Year Founded:** 1993 - **HQ Location:** Redwood City, CA - **Twitter:** @Informatica (99,880 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3858/ (5,337 employees on LinkedIn®) - **Ownership:** NYSE: INFA **Reviewer Demographics:** - **Top Industries:** Information Technology and Services, Computer & Network Security - **Company Size:** 40% Enterprise, 33% Small-Business ### 7. [Clonetab](https://www.g2.com/products/clonetab/reviews) Clonetab is a global enterprise dedicated to offering comprehensive solutions for many Database Administration needs. Our suite of products (The Database Administration Powerhouse) can serve as your virtual database administrator, streamlining tasks such as Virtualization, Rapid ERP and database Cloning, Data Scrambling, Disaster Recovery for Oracle EBS & Database, Lift and Shift for Oracle EBS & Database, SQL Self Service, Oracle EBS and Oracle Peoplesoft Snapshots, Database Patching (Fleet Patching) and Oracle EBS cloning on Oracle Exadata etc. Additionally, our remote database services encompass a wide range of DBA activities, empowering companies to transition to more efficient, automation-driven database management. **Average Rating:** 4.4/5.0 **Total Reviews:** 48 **User Satisfaction Scores:** - **Ease of Admin:** 9.2/10 (Category avg: 8.6/10) - **Static Masking:** 8.6/10 (Category avg: 8.5/10) - **Dynamic Masking:** 8.7/10 (Category avg: 8.4/10) - **Sensitive Fields:** 8.5/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Clonetab](https://www.g2.com/sellers/clonetab) - **Year Founded:** 2011 - **HQ Location:** Tracy, California - **Twitter:** @Clonetab (17 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/clonetab-inc-/ (66 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 54% Small-Business, 29% Mid-Market ## Parent Category [Data Security Software](https://www.g2.com/categories/data-security) ## Related Categories - [Database Security Software](https://www.g2.com/categories/database-security) - [Data De-Identification Tools](https://www.g2.com/categories/data-de-identification) - [Sensitive Data Discovery Software](https://www.g2.com/categories/sensitive-data-discovery) --- ## Buyer Guide ### What You Should Know About Data Masking Software ### What is Data Masking Software? Data masking is a technique used by organizations to protect sensitive data from unintended exposure. Data masking is also sometimes referred to as data obfuscation. There are a number of masking techniques, including data substitution, data shuffling, translating numbers into number ranges, nulling or deletion, character scrambling, and more. Companies use data masking software to shield sensitive data such as personally identifiable information (PII) or sensitive customer information while maintaining the data’s functional value.  Data masking software ensures that unauthorized people do not have visibility into real, sensitive data records by masking the data. Companies commonly utilize data masking to limit the sensitive data visible to their employees. This protects against both employee mistakes in handling sensitive data and malicious insider threat actors seeking to steal sensitive information. For example, credit card numbers in a database can be redacted or replaced with false data in a billing software application so that the real numbers are not exposed and visible to frontline employees. A masked credit card number would be structurally similar and maintain the sixteen-digit credit card number format of "xxxx-xxxx-xxxx-xxxx" that the company’s billing software application expects this data to be in, while not providing the actual credit card number.  A common use case for data masking is providing non-production but realistic data for software development and testing. Applications must be developed and tested using real data to ensure the software meets the company or customer’s needs, but providing sensitive data to a development team exposes the data to people who don’t need to be authorized to view it. For example, if an educational software company is developing a solution to manage student testing data, having specific individuals’ testing information like real names, addresses, test scores, academic grades, and so on is not necessary to develop the tool. Having data based on real data but scrambled or obfuscated is sufficient to test the software. As long as the data is functionally correct, the software developers don’t need to know the precise, sensitive data to develop and test the software solution.  Data masking is most often for non-production purposes like software development and testing mentioned above, but it can also be used in production environments to control which users have access to sensitive information. For example, employees in a call center may need to look up a customer’s account information in a CRM software to process a payment but do not need access to the customer’s exact payment details like bank account and routing numbers to complete the transaction. The company must retain the actual bank account information to process the transaction, but this sensitive information does not need to be visible to the call center employee, so the company masks that data for the call center employee in their call center software application. Other use cases for using masked data include: - Sales demonstrations of software programs - User training modules - Sandbox experiments ### What Types of Data Masking Software Exist? **Static data masking** Static data masking solutions allow sensitive datasets to be masked while the data is at rest. This usually entails a complete copy of a masked dataset. Most commonly, this is used for non-production use cases like providing datasets for software development and testing purposes. **Dynamic data masking** Dynamic data masking solutions allow sensitive data to be masked while the data is in use, and the masking can be based on the attributes of the person viewing it. Most commonly, this is used for in-production use cases. For example, frontline employees or employees in a specific geographic area can view the sensitive dataset dynamically masked based on their role type in real time. This software can be particularly beneficial for customer service use cases. ### What are the Common Features of Data Masking Software? The following are some core features within data masking software that can help users achieve their business goals: **Performance with large datasets:** Data masking software must be able to meet the scale and speed of masking large datasets, whether the masking is performed on the database level itself, between application layers, or within the application itself. This is especially important for masking enterprise data and big datasets. **Preserving data characteristics:** Some applications expect data to be in a specific format, such as a 16-digit credit card number. For masked data to be utilized in the application, the masked data must also conform to these data characteristics like number length. **Deterministic masking:** Deterministic masking allows for the masked data to be consistently masked across multiple tables and applications. For example, if a data record has a first name of “Joan” then the masked name of “Claire” will appear consistently and uniformly across the masked dataset and applications it is used in. This is important especially for in-production customer service use cases where company employees interact with multiple applications like CRMs and billing applications to assist customers. Having consistently matching masked data in those disparate applications can aid in providing the best customer assistance. **Cloud-compatible data masking** : Today, many companies are shifting from on-premises data stores to the cloud and are utilizing infrastructure as a service, platform as a service, and software as a service tools. Many data masking tools offer solutions to protect data regardless of where it is used. ### What are the Benefits of Data Masking Software? **Reduce unintended data exposure:** The main purpose of using data masking software is to protect the data from unintended exposure while maintaining the data’s usability. Data masking software obfuscates the data for audiences that are not authorized to view the data.  **Improve access control to data** : Data masking software enables companies to only expose data on a need-to-know basis. Using dynamic data masking, in particular, can assist a company with enabling role-based data visibility. So a frontline worker may not be able to see specific customer data like their billing address or phone number within a CRM application, but their manager would have the authorization to do so. **Meet data protection compliance regulations** : Data protection regulations and data privacy laws require businesses to safeguard data such as personally identifiable information. Data masking is a technique used to limit unintended data exposure and meet data protection by design and default requirements. Data masking can assist in meeting industry or governmental regulations such as GDPR, PCI DSS, or HIPAA. ### Who Uses Data Masking Software? **InfoSec and IT professionals** : Information security (InfoSec) and IT professionals implement and manage data masking tools to achieve their company’s data security, data privacy, and data usage goals. **Software developers** : Software developers are the end users of data masked using data masking software. Using masked data allows software developers to use test data based on real data but without the risk of using plain text. **Frontline employees** : Frontline and other employees use masked data in their day-to-day interactions in the business applications necessary to complete their work. Having masked data in their applications protects them from accidentally viewing, sharing, or using data they are not authorized to use. ### What are the Alternatives to Data Masking Software? Alternatives to data masking software can replace this type of software, either partially or completely: [Data de-identification and pseudonymity software](https://www.g2.com/categories/data-de-identification-and-pseudonymity): De-identification and pseudonymity software is similar to data masking software in that it focuses on anonymization by replacing real data with artificial data. However, the difference shows in the end states; data masking obfuscates the data while retaining the original data, while de-identified data is not masked but de-identified through pseudonymization to prevent re-identification. [Synthetic data software](https://www.g2.com/categories/synthetic-data): Synthetic data software helps companies create artificial datasets, including images, text, and other data from scratch using computer-generated imagery (CGI), generative neural networks (GANs), and heuristics. Synthetic data is most commonly used for testing and training machine learning models. [Encryption software](https://www.g2.com/categories/encryption) **:** Encryption software protects data by converting plaintext into scrambled letters known as ciphertext, which can only be decrypted using the appropriate encryption key. Most commonly, encrypted data cannot be used within applications and must first be decrypted prior to use within applications (with some exceptions with homomorphic encryption techniques).  #### Software Related to Data Masking Software Related solutions that can be used together with data masking software include: [Sensitive data discovery software](https://www.g2.com/categories/sensitive-data-discovery): To determine what data to protect using data masking software, companies must first identify their sensitive data. Companies can use sensitive data discovery software to assist in and automate that process. These solutions search structured, unstructured, and semi-structured data stored in on-premises databases, cloud, email servers, websites, applications, etc. ### Challenges with Data Masking Software Software solutions can come with their own set of challenges.  **Sensitive data discovery** : To protect data using data masking techniques, the data a company wants to protect must first be identified. The type of data that companies seek to mask can include personally identifiable information (PII), protected health information (PHI), payment card industry (PCI) data, intellectual property (IP), and other important business data. Often, this data is stored across multiple company systems, including databases, applications, and user endpoints.  **Defining role-based-access policies:** Using dynamic masking that modifies what data is masked or visible based on a viewer’s role type requires those roles to be defined by company policy. This requires companies to invest in defining those roles for the data masking software to be effective. **Re-identification:** A common concern of using masked data is the risk of it being re-identified using other context clues resulting in a data breach. This could be by combining the data with other datasets to re-identify it or simply by not masking enough data. For example, in a CRM system, if a customer’s first and last name is redacted, but not their email address, which is often a person’s first and last name, it can be easy to infer who the customer is. ### How to Buy Data Masking Software #### Requirements Gathering (RFI/RFP) for Data Masking Software Users must determine their specific needs to prepare for data masking. They can answer the questions below to get a better understanding: - What is the business purpose?  - Does the user need static data masking solutions, or do they need dynamic data masking solutions? - What kind of data is the user trying to mask?  - Is it financial information, classified information, proprietary business information, personally identifiable information, or other sensitive data? - Have they identified where those sensitive data stores are--on-premises or in the cloud? - What specific software applications is that data used in?  - What APIs do they need?  - Who within the company should have the authorization to view sensitive data, and who should be served masked data?  #### Compare Data Masking Software Products **Create a long list** Buyers can visit g2.com’s[](https://www.g2.com/categories/data-masking)[Data Masking Software](https://www.g2.com/categories/data-masking) category, read reviews about data masking products, and determine which products fit their businesses’ specific needs. They can then create a list of products that match those needs. **Create a short list** After creating a long list, buyers can review their choices and eliminate some products to create a shorter, more precise list. **Conduct demos** Once a user has narrowed down their software search, they can connect with the vendor to view demonstrations of the software product and how it relates to their company’s specific use cases. They can ask about the masking methods--from substitution to shuffling and more, and where their solution sits--at the database level, between the application and the database, or within the application. Buyers can also ask about integrations with their existing tech stack, licensing methods, and pricing—whether fees are based on the number of projects, databases, executions, etc. #### Selection of Data Masking Software **Choose a selection team** Buyers must determine which team is responsible for implementing and managing this software. Often, that may be someone from the IT team and the InfoSec team. They should also include end users on their selection team, such as software developers or frontline employees. It is important to have a representative from the financial team on the selection committee to ensure the license is within budget.  **Negotiation** Buyers should get specific answers to the cost of the license and how it is priced, and if the data masking software is based on database size, features, or execution. They must keep in mind the company’s data masking needs for today and the future. **Final decision** The final decision will come down to whether the software solution meets the technical requirements, the usability, the implementation, other support, expected return on investment, and more. Ideally, the final decision will be made by the IT team in conjunction with InfoSec or data privacy teams, alongside input from other stakeholders like software development teams.