QubeAxis Product

Built for Every Byte
that Matters — Data Quality Validator

A complete data processing platform for modern enterprises. Engineered to ensure quality at every stage — compare, migrate, mask, validate, and generate production-grade synthetic data with speed and confidence.

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✓ Field by field comparison ✓ Secure masking ✓ Large dataset support ✓ HIPAA / GDPR ready

Data quality and speed with security

One cohesive platform for comparison, migration, masking, validation, and synthetic data generation.

Core Capabilities

Powerful features designed to deliver

Five integrated modules covering every stage of your data pipeline — from field-level comparison to production-grade synthetic data generation.

Compare — Field by Field Comparison

Compare data sets with precision using field-level matching, summary mismatch reporting, and memory-efficient processing for large volumes — even across different schemas.

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Different structuresCompare tables, files, and records even when schemas differ.

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Memory efficientOptimized processing designed for very large datasets.

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Field-level diffHighlights every mismatch and supports quick decisions.

📝

Mismatch summaryConcise summary plus full detailed reporting output.

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Migrate — Flawless and Quick Migration

Enable data aggregation, filtering, field mapping, deterministic masking, and calculated field creation for reliable migration between any systems or environments.

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Field mappingMap source and target fields with flexible transformation logic.

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Aggregation & filteringPrepare and reshape data before moving it.

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Deterministic maskingProtect sensitive data while preserving consistency.

⚡

Calculated fieldsCreate derived values with controlled business rules.

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Mask — Protect Sensitive Data

Implement in-place and in-flight masking with repeatable algorithms, redaction, replacement, and privacy-first workflows built for HIPAA and GDPR compliance.

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In-place & in-flightMask data before or during movement across environments.

♻️

Repeatable maskingDeterministic algorithms keep outputs consistent every time.

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Redaction & replacementMultiple masking techniques for different use cases.

📜

Privacy readySupports HIPAA and GDPR-oriented data handling standards.

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Validate — Check Quality of Data

Run high-performance data quality validation at field, record, and table levels with systematic error collection, on-the-fly diagnostics, and comprehensive reporting.

✓

Record-level validationFind errors with structured, meaningful diagnostics.

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Table-level checksValidate totals, completeness, and referential integrity.

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On-the-fly collectionCollect issues while validating for immediate action.

📈

ReportingProduce audit-friendly summaries for teams and stakeholders.

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Synthetic Data — Production-Grade Generation

Generate meaningful names, addresses, IDs, numeric sequences, and string lists for realistic testing without ever exposing real or sensitive production data.

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Meaningful recordsName, address, SIN, SSN, and business-ready structures.

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Numerical valuesSequential or random values within any chosen range.

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String generationSequential or random list-based string data outputs.

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Business rulesIdeal for test suites, analytics, and QA environments.

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Benefits

Unlock powerful business value with DQV

Data integration and validation that optimises quality while supporting growth, compliance, and speed.

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💰

Cost Reduction & ROI80–90% lower TCO, no consultant dependency, runs on standard hardware.

⚡

Efficiency & Productivity90%+ faster validation, zero manual errors, 100% dataset coverage with parallel processing.

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Risk & QualityZero data loss migrations, detect issues early, validate at every level.

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Compliance & PrivacyHIPAA/GDPR-ready, secure data masking, flexible privacy options.

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Digital TransformationFaster time-to-market, legacy-to-cloud ready, CI/CD integration support.

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Scalability & Readiness15x performance boost, any database or format, future-proof architecture.

Data quality, speed, and security in one platform

Designed to reduce manual work, improve reliability, and ensure accurate reporting across migration, test automation, analytics, and enterprise compliance programs.

Lower TCOLess tooling, less effort, more repeatability.

Better CoverageValidate complete datasets with confidence.

Cleaner ReleasesCatch issues before they reach production.

Secure by DesignMask and protect sensitive data end-to-end.

User Application

The right fit for every team

DQV helps different roles across engineering, QA, operations, and data teams work faster and with more confidence.

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ETL TesterCreates realistic test datasets, finds missing data, validates incoming quality, compares source and target datasets, and generates synthetic data for testing.

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DBASupports in-flight and in-place masking, data migration, integrity checks, and regulatory compliance across environments.

👨‍💻

DeveloperImport/export data easily, validate inputs, identify invalid or missing values, compare datasets, and generate synthetic test data.

✅

Functional QAGenerates test data from existing records, compares datasets and files, and continuously monitors quality across releases.

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API TesterGenerates synthetic data, mimics data flow, compares expected versus actual results, and keeps analytics inputs clean.

Supported Data Sources

Expertise that drives excellence in automation

🗄️

Database

SQL Server, Oracle, MySQL, PostgreSQL

Work across mainstream relational databases with a single validation approach.

📄

Files

CSV, Delimited, Fixed Length, Excel

Validate structured file data from spreadsheets and fixed-format exports.

☁️

Cloud Databases

AWS, Azure, Google Cloud

Designed for modern cloud data platforms and enterprise deployment needs.

🔗

Connectors

REST APIs, Message Queues

Connect directly to application interfaces and event-driven data flows.

🧾

Data Format

JSON, XML, Parquet

Support for modern structured and semi-structured data formats.

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Extensible

Custom connectors available

Extend the platform to fit your environment and unique integrations.

Technical Questions Answered

Frequently asked questions

Helpful answers for migration, compliance, synthetic data, integrations, and large-scale processing.

DQV provides pre- and post-migration validation, field-level comparison, discrepancy highlighting, and detailed reporting so teams can verify the source and target are fully aligned before go-live.

You can use field mapping, transformation rules, calculated fields, and filtering to reconcile differences across schemas and still validate the output accurately.

Yes. DQV supports deterministic, in-place, and in-flight masking, with redaction and replacement options to protect privacy-sensitive records under HIPAA and GDPR requirements.

It is designed specifically for large data with memory-efficient processing, field-by-field comparisons, parallel execution, and high-performance validation workflows.

DQV generates production-grade synthetic values such as names, addresses, IDs, numeric ranges, and list-based strings that are fully aligned with your business rules and data structures.

Yes. DQV is built to integrate with cloud databases, REST APIs, message queues, and ETL workflows through flexible connectors and deployment options across AWS, Azure, and Google Cloud.