Copying production data to non- production environments?

A Patented, All-in-one Data Security Platform for PCI Compliance

Create high-fidelity test data to limit the risk of production data exposure in non-production environments.

Trusted by Enterprises Worldwide

Protect your non-production environment from production data

Non-production environments, for any number of reasons, can be vulnerable, risking any production data that may be used to test inside them. Our Test Data Management solution anonymizes production data to be safely used in non-production environments. Test accurately, without the risk of data exposure.

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Anonymization: Convert sensitive data from your prod environment to non-prod environments with meaningful substituted values. (The icon is a browser with an eye crossed out)

Referential integrity: Consistent, repeatable replacements across data sources to ensure business logic or test scripts just work. (The icon is a File with a document in it)

Existing or Synthetically Created Datasets: Create data based on existing customer sets or none at all. (The icon is a document with portraits of people and information and an arrow from it pointing to a database icon)

Representative High-Fidelity Test Data: Build test data sets that accurately represent characteristics and trends in existing data sets. (The icon is a document with a checkmark)

No Data Set Duplication: real-time tokenization removes the need to duplicate large data sets before creating test data. (Icon is two documents and one with a small “X” on it”

Test faster with fake data

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Scale Easily

Create test data in real-time, with no duplication and virtually no latency.

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Test with Confidence

With high-fidelity, referential test data that acts like real data, you can ensure your non-production environments are operating as they should be.

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Reduce Testing Risk

Never let the integrity of non-production environments impact your data security.

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Host Anywhere

Use the same process to generate data in any location, including ingestion pipelines for big data and cloud analytics on-prem or in the Cloud.

Components and Functionality

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Filter and Subset

Use lookup and row data to filter and subset data to create variable sized data sets while ensuring referential integrity.

Script and API Execution

Use custom scripts to manipulate data, and make calls out to APIs to get data or trigger business processes.

Business and Referentially-Aware Subsetting

Apply business logic and integrity, supporting multi-table "joins" to apply intelligent replacements.

Transfer Schema and Data

Extracts and creates database structure to avoid restoring databases to apply de-identification.