AI Powered Production Realistic Test Data

Test Data For Your QA Team Without Any Compliance Risk

Q: How is it different from manually anonymising production data?

Manual anonymisation is error-prone and one-time. TDM uses AI to detect PII automatically, applies column-level masking, and refreshes automatically. One missed column in a manual process = a GDPR breach. See compliance solutions →

Generate synthetic test data that mirrors production, mask sensitive fields automatically, and give your team Production Realistic Test ability— without copying real PII or PHI into non-production environments.

What We Keep Hearing

“What we've tried in the past was to start with an empty schema and then load synthetic data into it, but that's very difficult to do because of relational constraints”

“I have 1,400 tables with all related tables. It's not that easy to generate test cases — I need a coverage scenario for policy, scenario by scenario.”

“The state of the data starts to be more and more a mess — more and more complex to find the right data.”

That’s Why We Built Test Data Manager

Test Data Management in Act

Test Data Problems We Solve at Scale

How We Solve Them Differently

From Testing bottlenecks to readiness

Expected Business Outcomes

90%

Faster test
data provisioning

100%

PII/PHI masked
before QA exposure

60%

Reduction in
test data prep effort

TDM Overview

Test Data Manager (TDM) is an AI-powered solution that generates realistic, privacy-safe synthetic data for testing applications, ETL pipelines, and BI platforms. It automates data discovery, masking, and generation, supports enterprise-scale deployments, ensures regulatory compliance, and enables faster, secure, production-like testing without exposing sensitive data.

This helps organizations test faster without exposing sensitive data — giving every stakeholder, from QA engineers to compliance officers, confidence in how test data is created and used.

Built In AI for Scale

Intelligent automation for realistic, privacy-safe test data

Automate Your Test Data Requirement with Scale & Compliance

Test Data Manager covers every test data need — generation, masking, and provisioning — before sensitive data ever reaches a QA environment.

Works With Your Entire Data Stack

Inside the TDM Engine: Discover, Mask, Generate

Three engines, one metadata layer — so what discovery finds, masking protects and generation respects.

Why is Test Data Manager the Best Among Test Data Management Tools?

Privacy & Compliance

AI Powered Synthetic Data Generation & Coverage

Self-Service Provisioning & Management

Every Test Data Scenario — Proven Across Industries

TDM is purpose-built for the scenarios that matter most to enterprise data teams.

Generate masked transaction and account data for testing under your organization’s financial-services privacy and security requirements — without copying real account numbers into QA.

Create HIPAA-compliant synthetic patient data for testing HL7/FHIR pipelines with zero PHI exposure.

Generate realistic supply chain, demand, and pricing test data — without relying on live production copies across systems.

Generate realistic test data for enrollment, financial aid, and research systems — without exposing student records in non-production environments.

Generate synthetic policy, claims, and endorsement data across complex, interrelated schemas — reducing reliance on copied production data.

Generate realistic inventory, pricing, and transaction test data at the volume your test environments actually need.

Don’t see your industry? Talk to our team →

Test Data Manager vs. The Alternatives

See exactly how TDM compares to manual testing and generic TDM across the capabilities that matter

Technical Capability	Datagaps TDM	Traditional TDM Tools	Custom Built Tool from LLM
Data Discovery / PII Detection	Rule-based + classical NER (column-name heuristics, regex/checksum validators, statistical inference, Presidio)	Varies by vendor — regex/dictionary-based, some with NER add-ons	Hand-coded regex/dictionary; no coverage guarantees
Data Generation	Relationship-aware synthetic generation from production patterns	Rule-based templates	Hand-coded generators
Referential integrity	Preserved automatically	Often breaks on complex schemas	Manual mapping required
Provisioning	Self-service, on-demand	Ticket-based requests	Ad hoc scripts
Compliance coverage	GDPR / HIPAA / CCPA	Varies by vendor	Difficult to comply
Time to value	Days	Weeks	Months
Ongoing maintenance	Vendor-maintained	Vendor-dependent	Engineering hours + key-person risk

What Data Leaders Are Saying About Datagaps

Verified reviews from data professionals on Gartner Peer Insights™

Gartner® and Peer Insights™ are trademarks of Gartner, Inc. and/or its affiliates. All rights reserved. Gartner Peer Insights content consists of the opinions of individual end users based on their own experiences, and should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose

Get Started Today

See Test Data Manager in Action

Reduce the manual effort behind test data preparation — get your 14-day free trial now.

SOC 2 Type II certified | ISO 27001 certified | No credit card required for trial | Your data never leaves your environment

FAQ's about Test Data Manager

Common questions from Enterprise Buyers

What does Test Data Manager do?

TDM generates production-realistic, PII-masked test datasets from your source systems — GDPR, HIPAA, and PCI-DSS compliant by design. AI detects sensitive columns and provisions datasets on demand. Explore Test Data Manager

Which compliance standards does it support?

HIPAA, GDPR, CCPA, and PCI-DSS — with deterministic, reversible, or random masking by column type. SOC 2 Type II and ISO 27001 certified. Sensitive data never leaves your environment. View compliance details

How does AI-powered PII detection work?

AI identifies sensitive columns by data type, naming patterns, and content before masking begins — automatically catching what manual column-by-column review misses. Masking rules are then configurable per column. Start free trial

Can Test Data Manager generate data for AI/ML model training?

Yes. TDM generates clean, schema-consistent, statistically valid synthetic datasets at scale — preserving production distributions and edge cases without exposing real customer data or violating privacy regulations. Explore DataOps Suite

Does it preserve referential integrity in masked datasets?

Yes. All primary key, foreign key, and parent-child relationships are preserved in masked data — so test environments behave exactly like production, including complex multi-table joins and dependency chains. See how TDM works

What data formats and sources does it support?

Oracle, SQL Server, PostgreSQL, Snowflake, SAP HANA, and more via JDBC — plus JSON, XML, CSV, and hierarchical formats. Generates millions of records from small production samples. No connector engineering required.

How does it integrate with CI/CD and dev/QA workflows?

TDM auto-provisions test data on pipeline triggers — dev and QA always have current, compliant, production-realistic data. No manual export requests, no waiting, no stale datasets. Explore DataOps Suite integration

How is it different from manually anonymizing production data?

Manual anonymization is error-prone and one-time. TDM uses AI to detect PII automatically, applies column-level masking, and refreshes automatically. One missed column in a manual process = a GDPR breach. See compliance solutions

Which industries benefit most from Test Data Manager?

Healthcare (HIPAA-compliant PHI masking), Financial Services (PCI-DSS account masking), and Retail (GDPR/CCPA). See Healthcare, Financial Services, Life Sciences use cases.

How does Test Data Manager work with ETL Validator?

TDM is natively integrated in the DataOps Suite — masked datasets flow directly into ETL Validator for pipeline testing. One platform. No data hand-off risk. No compliance gaps between test data and validation.

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Test Data For Your QA Team Without Any Compliance Risk

What We Keep Hearing

“What we've tried in the past was to start with an empty schema and then load synthetic data into it, but that's very difficult to do because of relational constraints”

“I have 1,400 tables with all related tables. It's not that easy to generate test cases — I need a coverage scenario for policy, scenario by scenario.”

“The state of the data starts to be more and more a mess — more and more complex to find the right data.”

That’s Why We Built Test Data Manager

Test Data Management in Act

Test Data Problems We Solve at Scale

Long Wait Times for Usable Test Data

Compliance Risks from Production Data

Synthetic Data Breaking on Complex Schemas

Audit Risk Due to Limited Transparency

How We Solve Them Differently

From Testing bottlenecks to readiness

Expected Business Outcomes

90%

100%

60%

TDM Overview

Built In AI for Scale

AI-Powered PII & PHI Detection

Production-Realistic Synthetic Data

Policy-Driven Data Masking

Automate Your Test Data Requirement with Scale & Compliance

Works With Your Entire Data Stack

Inside the TDM Engine: Discover, Mask, Generate

Discovery finds what manual review misses.

Masking acts on exactly what discovery found.

Generation inherits both.

Why is Test Data Manager the Best Among Test Data Management Tools?

Privacy & Compliance

GDPR‑Compliant Test Data Management

Dynamic Data Masking

Consistent Test Data Governance Across Environments

AI Powered Synthetic Data Generation & Coverage

Synthetic Data Generation

Complete Test Coverage with Synthetic Data

Relationship‑Aware Synthetic Test Data

Self-Service Provisioning & Management

Self‑Service Test Data Management

On‑Demand Test Data Provisioning

Automated Data Pipeline Testing