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Apica

Test Data Orchestration

Self-Service Test Data for Accelerated Software Delivery

Test data management is a critical bottleneck in modern software delivery. Development and QA teams can wait days or weeks for centralized teams to provision test environments, slowing release cycles and reducing agility. When data finally arrives, it’s often an oversized production copy, creating 10x larger footprints that inflate cloud costs and increase privacy risks.

Apica’s Test Data Orchestrator (TDO) eliminates these bottlenecks with self-service automation, synthetic data and AI-powered intelligence. Teams provision right-sized, compliant test data on demand, no coding required, no waiting for central teams.

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The Challenge

Manual Test Data Creates Release Bottlenecks

Extended Wait Times and Sequential Dependencies

Traditional test data management relies on centralized teams with specialized skills. Development and QA teams submit requests and wait, often 2-3 weeks, for data provisioning. This sequential process creates cascading delays: testing can’t start until data arrives, deployments wait for testing completion, and release dates slip.

Oversized Data Footprints Drive Up Costs

Non-production environments typically replicate broad swathes of production data without intelligent subsetting. A database with 10 million production records is copied in its entirety, or at 10% scale (1 million records), when only 21,400 records are actually needed for comprehensive test coverage. This creates 10x larger footprints across multiple environments (development, QA, UAT, staging), exponentially increasing cloud storage costs.

Privacy Risks in Non-Production

Most data breaches occur in non-production environments because controls are weaker and data surface areas are larger. When non-production footprints are 10x production size, the potential breach surface area is exponentially larger, yet these environments often lack production-grade security controls. The advent of AI both increases and exposes these risks much more quickly, as AI Agents scanning data sources routinely come across sensitive data which should have been masked in non-Production environments.

Incomplete Test Coverage Allows Defects

When test data provisioning is slow and expensive, teams resort to risk-based testing instead of full coverage. Edge cases go untested, defects leak into production, while the cost of fixing production issues far exceeds the cost of comprehensive pre-production testing.

Limited Data for Migrations and New Builds

Platform migrations, cloud migrations, and greenfield projects face a chicken-and-egg problem: They need test data, but production data doesn’t exist yet in the correct format. Traditional approaches can’t generate valid synthetic data for complex workflows, creating project delays.

Our Solution

Self-Service Test Data Orchestration

Criteria-Driven Self-Service Automation

TDO transforms test data from a centralized service to a self-service capability. Development and QA teams input criteria through an intuitive interface, no coding required. TDO workflows then automatically profile production data, generate exact data subsets, mask sensitive information, and generates synthetic data to fill gaps in minutes to hours instead of weeks.

Intelligent Data Subsetting Reduces Footprints by 90%+

TDO profiles production data sources to identify valid patterns and relationships. Instead of copying 10 million production records, TDO generates exact data requests that extract only the e.g. 21,400 records needed for comprehensive test coverage, a 99.8% reduction. This dramatically reduces non-production storage costs while actually improving test quality.

AI-Powered Synthetic Data with Explainable AI

For gaps in production data, migrations, or regulatory requirements, TDO generates referentially-intact synthetic data using explainable AI (XAI). Unlike black-box approaches, TDO creates transparent, reusable frameworks that users can see, control, and update. The AI doesn’t need external hosting, it can be deployed in your environment. TDO maintains context and learnings across cycles, unlike competitors that regenerate from scratch. This approach enables TDO to generate complex synthetic data which works end to end in integrated environments, and which aligns automatically with any masked Production data also in use.

Automatic Masking Minimizes Privacy Risks

TDO filters and masks data before loading into non-production environments. Combined with intelligent subsetting and synthetic data, this reduces data breach surface area by up to 100%+, making non-production environments exponentially more secure. When the size of data has been so dramatically reduced, masking (de-identification) takes much less time. There is simply no reason not to do it as part of an automated, criteria-driven workflow.

API-Driven CI/CD Integration

TDO is fully API-enabled for DevOps workflows. Teams automate data refresh on every build or deployment, enabling true continuous testing practices without manual intervention.

Business Value

Accelerated Delivery with Reduced Risk

Quantifiable Benefits

  • 90%+ reduction in test data provisioning time: From days/weeks to minutes/hours with self-service automation
  • 90%+ reduction in non-production data footprints: 10M records → e.g. 21K records through intelligent subsetting
  • 60-80% reduction in storage costs: Eliminate unnecessary cloud data footprints across multiple environments
  • 40-60% acceleration in release cadence: Remove test data bottlenecks from software delivery pipelines
  • Eliminate defect leakage: Enable full test coverage instead of risk-based testing
  • 90%+ reduction in breach surface area: Through intelligent subsetting and production-quality synthetic data the surface area is drastically reduced.
  • 100% PII Protection – Combine intelligent subsets, production-quality synthetic data with automated masking in Self-service workflows using TDO and eliminate PII risk.

Strategic Business Impact

  • Faster time to market: Eliminate sequential bottlenecks, enable parallel development
  • Improved agility: Self-service capabilities empower teams to move at their own pace
  • Better compliance: Automated masking, reduced footprints and high quality synthetic data minimize regulatory risks
  • Higher quality: Full, executable test coverage prevents production defects
  • Lower TCO: Reduce storage costs, operational overheads, and production incident costs
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Implementation

Four-Week Deployment Path

  • Deploy TDO instance in test environment
  • Confirm key data sources and secure access
  • Configure connections to key data sources
  • Define initial user roles and access controls
  • Set up Scenarios in TDO
  • Profile production data to identify patterns and relationships
  • Identify Sensitive Data (PII / PHI)
  • Capture or generate Business Rules which drive Test Coverage
  • Define and masking rules
  • Set up workflows to manage sub-setting and masking
  • Generate initial data subsets and validate coverage
  • Fine-tune subsetting rules based on team feedback
  • Configure synthetic data generation for gaps
  • Validate referential integrity across databases
  • Set up API connections for CI/CD integration
  • Test self-service workflows with development teams
  • Train development and QA teams on self-service interface
  • Optimize performance and storage configurations
  • Document best practices and common workflows
  • Calculate actual cost savings based on reduced footprints
  • Establish ongoing support and expansion plan

Key Differentiators

Why TDO vs. Traditional TDM

Pioneered Self-Service Test Data

TDO pioneered the criteria-driven approach where users input requirements, and the system automatically generates test coverage and data requests; and enables teams to manage their own Data Refresh on demand. Competitors still require specialized skills and manual processes.

Explainable AI (XAI) for Synthetic Data

TDO’s XAI approach creates transparent, reusable frameworks that users control, unlike black-box synthetic data tools. This makes TDO compliant with BFSI and healthcare regulatory requirements (zero-risk AI). TDO is the only synthetic data tool that maintains context and learnings across cycles, accumulating business context and intelligence for rapid reuse.

Seamless Integration of Masked and Synthetic Data

TDO automatically aligns synthetic data with masked production data, giving users full control over which aspects are synthetic versus masked. Other tools require an either/or choice.

Complements Existing TDM Investments

TDO works with IBM Optim and other TDM tools to enhance their value rather than replacing them. This means no disruption to your existing processes. TDO will leverage what you have.

Agentic AI Architecture Alignment

TDO is agent-ready, prompt-compatible, and fully API-enabled, future-proof for agentic architectures like IBM watsonx Orchestrate. It provides an easy on-ramp and use case for organizations adopting agentic AI, with zero risk of impacting Production systems / processes.

Common Use Case Scenarios

Scenario 1: Accelerating Release Cycles for Enterprise SaaS

Challenge: A SaaS company with bi-weekly release cycles waits 2-3 weeks for test data provisioning, causing release delays and team idle time.

Solution: TDO enables self-service data provisioning. Development teams input criteria and receive right-sized test data in minutes / hours — no central team dependencies.

Result: Provisioning time reduced from 2-3 weeks to minutes / hours. Release cadence increased from bi-weekly to weekly. Non-production storage costs decreased 72%.

Scenario 2: Cloud Migration with Limited Test Data

Challenge: A financial services company migrating from mainframe to cloud lacks appropriate test data for validating the new platform.

Solution: TDO ingests database schemas and profiles available source data to establish patterns.  Generates referentially-intact synthetic data for the cloud environment.

Result: Migration testing started 6 weeks earlier than planned. Zero privacy risks from production data exposure. Full coverage validation before cutover.

Scenario 3: Compliance-Driven Data Minimization

Challenge: A healthcare company faces regulatory requirements that prohibit any use of production data in testing—even masked data isn’t permitted.

Solution: TDO generates fully synthetic data using XAI that maintains referential integrity and validates against production patterns—without exposing actual patient data.

Result: 100% compliant testing with zero privacy risks. Audit-ready documentation of synthetic data generation. Comprehensive test coverage without regulatory exceptions.

Scenario 4: DevOps Automation with CI/CD Integration

Challenge: A retail company wants automated test data refresh on every build but current TDM processes require manual intervention.

Solution: TDO integrates with Jenkins pipelines via API. Every build triggers automated data refresh—no human involvement required.

Result: True continuous testing achieved. Test environment data always current. Manual TDM overhead eliminated completely.

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Schedule a Technical Workshop

Free 2-hour workshop to analyze your test data processes, calculate projected ROI, and design TDO architecture for your environment.

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Start a Proof of Concept

Request a 3-week POC program to deploy TDO in your environment, or to be hosted in ours, validate your use case and technical proof points, and calculate actual cost savings.

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Technical guides, and user guides available in Apica Docs.

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Additional Resources

Documentation

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Technical Guide: Test Data Orchestration with TDO

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