Sold by: DataMasque
Deployed on AWS
AWS Free Tier
DataMasque for Guidewire Cloud enables insurers to de-identify sensitive Guidewire policyholder and claims data. DataMasque generates synthetically identical data that can be safely used across testing, analytics and AI use cases. Fully functional, realistic and privacy compliant.
3.5
Overview
Insurers need realistic policyholder and claims data to develop new capabilities, improve digital experiences, run analytics and power AI transformation. Using real production data outside of secure environments introduces significant privacy and compliance risk.
DataMasque for Guidewire Cloud enables insurers using the Guidewire Snapshot export service with DataMasque to irreversibly de-identify sensitive Guidewire data, producing synthetically identical data that can then be returned securely to sandbox environments. The result is high-fidelity data that supports development, AI experimentation and transformation without any of the privacy risks.
DataMasque automatically preserves referential integrity across policies, claims and related records, ensuring critical data relationships are maintained for end-to-end insurance workflow testing.
Highlights
- Guidewire Cloud customers deploy DataMasque within their secure AWS environment. A pre-configured automation takes a secure snapshot of the Guidewire instance and, using a pre-defined Guidewire Cloud ruleset, DataMasque replaces sensitive information with synthetically identical customer data.
- DataMasque can preserve referential integrity across Guidewire and other core systems. Policies, claims and related records remain connected and consistent, ensuring full utility and fidelity for end-to-end insurance workflow testing.
- DataMasque's synthetically identical customer data looks and behaves the same way as your real data, maintaining patterns, statistical accuracy and edge cases, without any sensitive information. Irreversible de-identification removes compliance friction from AI development, migrations, software development and third-party data sharing.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Rhel 9.4
Deployed on AWS
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Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
guidewire_tb | Guidewire TB | $25,000.00 |
Dimensions summary
This listing uses a single pricing dimension based on Guidewire TB, so you pay according to the volume of Guidewire Cloud data you mask, measured in terabytes. Pricing scales with the amount of data you process rather than by user count or number of masking runs. As your masked data volume grows, your cost adjusts to match. This is a contract-based purchase, so you commit to a term and settle billing through your AWS account for consolidated invoicing.
Top-of-mind questions for buyers
One unit equals one terabyte of Guidewire Cloud data that the software masks. Billing counts the volume of data processed, not the number of users, databases, or masking runs. As the volume of masked data grows, the number of terabyte units you consume increases accordingly.
You can perform masking runs on data of any size. Your cost tracks the terabytes of Guidewire Cloud data you mask, so running more or larger jobs raises the volume billed. There is no separate charge tied to the count of runs.
The software discovers and masks sensitive data using keyword and pattern searches. It applies irreversible masking through a salted cryptographic hash, keeps masked values consistent across sources, and maintains referential integrity for primary, unique, and foreign keys. It integrates with existing CI/CD tools through an API-first design.
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Vendor refund policy
Refunds and cancellations are not available.
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Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Image Masking for Unstructured Text
The unstructured_text mask can now mask PNG and JPEG images in files and binary columns. With image_handling set to mask, text in an image is read using optical character recognition (OCR) and then masked.
Apache Cassandra Connections
Apache Cassandra is now available as a database connection type.
SAP ASE Connections
SAP ASE (Sybase) is now available as a database connection type.
Salesforce Connections (Preview)
Salesforce is now a connection type for masking, discovery and ruleset generation on Salesforce orgs. It is a preview feature and stays off until an admin turns on Enable preview features.
Google Cloud Storage File Connections
Google Cloud Storage is now supported as a file connection type.
MySQL 9.7 Support
DataMasque now supports MySQL 9.7 as a data source.
PostgreSQL Array Column Masking
PostgreSQL array columns can now be masked, with each mask applied to each element of the array in turn.
Table Filtering for Discovery
A new tables option for database discovery configurations restricts a discovery run to tables matching schema-qualified glob patterns.
Improved Reliability Under Load
Masking and discovery runs, and the web UI, are now more reliable when DataMasque is busy or starting up.
PDF Text Fitting
PDF masking now scales replacement text horizontally to fit the width of the original text, so it no longer overlaps the text that follows.
In and Not In Comparisons for In-Flight Masking
In-Flight Masking rulesets now accept the in and not_in comparisons with a list of values. Table references are not supported for these comparisons.
Deep Foreign Key Chain Fix
Fixed masks such as imitate_unique and from_unique_imitate not updating tables more than one level down a chain of foreign keys, which left original values in place and dropped foreign keys. This also affected IBM Db2 LUW when a foreign key column name contains a space.
SQL Server Code Page Collation Fix
Fixed Microsoft SQL Server masking runs failing when a key column uses a code page 850 or 437 collation, such as SQL_Latin1_General_CP850_CI_AS.
MariaDB Stale Statistics Fix
Fixed MariaDB masking runs stalling on tables with out of date statistics, such as a table bulk-loaded shortly before a server restart.
PDF Hash Sources Consistency Fix
Fixed PDF masking with hash_sources giving the same value different replacements within one document when the text wraps across lines.
SSL Certificate Chain Fix
Fixed uploaded SSL certificate chain files serving only the leaf certificate, which caused API clients such as curl to fail certificate verification. Upload an affected chain file again to serve the whole chain.
Additional details
Usage instructions
Please follow the steps below to complete setting up your DataMasque instance:
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Access the application via a web browser at https://<instance-ip-or-hostname>. The application may take a few minutes to start. Please refresh the page if you encounter the "Unexpected Error" message.
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Complete the first-time installation page by providing the following information:
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Email address of the DataMasque admin user. This email address is stored on the DataMasque EC2 instance and is used for the purposes of providing 'Forgotten Password' account recovery and critical system notifications. DataMasque will not have access to this information.
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Password for the admin user.
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Hostnames or IP addresses to access the DataMasque instance.
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The SMTP settings specific to your organisation.
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The instance ID of your EC2 instance.
- You will be re-directed to the DataMasque login screen. Please proceed to login with the admin password you have just configured.
Note:
- When you use our software we may receive and store usage data and information relating to the performance and use of the Software. We will not disclose any system information which identifies the user or the user environment to third parties.
- To upgrade your DataMasque version, contact the DataMasque team via https://datamasque.com/contact/?source=support_ticket or support@datamasque.com to request your access to the DataMasque Customer Portal and download the new DataMasque software version.
Resources
Vendor resources
Support
Vendor support
DataMasque provides full product and installation support within 72 hours of making an enquiry. Contact the support team at support@datamasque.com for any enquiries you may have.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Shaikshavali K.
Best tool for data masking
Reviewed on Jan 26, 2024
Review provided by G2
What do you like best about the product?
I liked that way it was created to mask business and sensitive data with data masking.
What do you dislike about the product?
It should be better user friendly UI. Performance can also be improved better
What problems is the product solving and how is that benefiting you?
Hiding sensitive data and business data with some data masking techniques.