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Agentic AI-Powered · Low-Code · 200+ Connectors

ETL Testing & Data Validation Tool

Powered by Agentic AI

A purpose-built AI-powered ETL Test Automation for complex Data migrations and Data warehouse transformations with 100% Row Validation and self-healing tests in a low-code user interface

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Trusted by 100+ Leading Enterprises

ETL Validator Overview

ETL Validator offers a robust, scalable, and AI-powered solution for automated ETL testing and data quality management. It is designed to ease the complexities of validating data migration and transformation processes through extensive connectivity, automation, and user-friendly interfaces.

This helps organisations maintain high standards of data accuracy, consistency, and pipeline reliability.

datagaps dataops suite platform
gartner market guide

Datagaps is recognized as a data pipeline test automation specialist in Gartner's Market Guide for DataOps Tools

ETL Validation in Action

Problems We Solve at Scale

Migrations stall for weeks in QA

Manual testing consumes 60–80% of migration timelines, and hand-written SQL can't cover billions of rows — so go-live slips and budgets overrun.

Bad data hits production before you catch it

Spot-checking 5% of data leaves 95% untested. Defects surface in live dashboards and cost 10× more to fix and erode trust in every number.

One schema change breaks all your tests

Brittle, hand-maintained scripts force a rewrite with every pipeline change — so senior engineers maintain tests instead of shipping data.

No evidence when auditors come calling

Spreadsheet QA leaves no reproducible history or audit trail — a compliance gap that surfaces at the worst possible moment

How Do we solve Them Differently

From reactive correction to proactive data governance

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Catch defects before cutover — validate 100% of records, not samples, across any source-target pair.

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Cut migration QA from weeks to days — AI generates test cases from your mapping docs in minutes.

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Stop rewriting tests — self-healing validations adapt automatically when schemas change.

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Pass every audit — downloadable, audit-ready evidence generated on every run, automatically.

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Make testing continuous — native CI/CD integration bakes validation into every deployment.

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Validate at any scale — parallel execution compares billions of rows in minutes, not hours.

See How It Works

Business Outcome We Delivered

500B+

Records Validated
Across ETL

10M+

Automated Test
Cases Run

80%

Faster Test Cycles
vs. Manual Testing

70%

Reduction In ETL
Validation Spend

Automate Every ETL Test and Verify 100% of Your Data

ETL Validator covers every validation need – completeness, accuracy, and transformation logic across source and target before bad data reaches dashboards, models, or decisions.

Works With Your Entire Data Stack

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100% Row Coverage — Not Sampling

Datagaps’ US-patented ELV architecture validates every record across 200+ systems. No blind spots. No gaps.

AI Turns Your Mapping Spec Into a Test Suite — Instantly

Upload your source-to-target mapping doc; AI auto-generates every test case. 100 tables: hours, not weeks.

Your Data Never Leaves Your Infrastructure

Comparison SQL runs inside your own Snowflake, Databricks, or Oracle. Zero data exposure. Compliant by design.

How ETL Validator Works

From connecting your first source to a fully automated validation pipeline — in five steps, live within days.

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Connect Sources

200+ connectors, auto schema sync

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Generate Tests

AI-built test cases, no SQL

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Run & Schedule

Scale to billions of rows, any CI/CD

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Review Results

AI-explained exceptions, row-level detail

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Certify & Ship

Audit-ready reports, compliance sign-off

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Why Is ETL Validator The Best Among ETL Testing Tools?

Connectivity & Low‑Code Test Design

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Connect to 200+ Data Sources

Supports legacy and modern sources including Snowflake, Databricks, and file sources like AWS S3, ADLS, and GCS.

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Low-Code Visual Test Case Builder

Drag-and-drop visual builder with query builder to define tests without manually typing queries.

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No-Code ETL Validation

Accelerate ETL test creation with AI agents that automate routine validation tasks while allowing Python and SQL for deeper, code-level control.

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ETL Validator -Connectivity & Low‑Code Test Design

Automated & Scalable Data Validation

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Scalable ETL Testing Automation

Scale ETL validation through parallel execution to compare large volumes across sources and shorten test cycles significantly.

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Flat File Testing

Validate incoming flat files with column-level rules. A built-in file watcher detects new files and automatically triggers tests.

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Incremental ETL Testing

Validate daily delta changes and perform targeted record verification to accelerate high-volume ETL testing cycles and cut down overhead costs.

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Automated & Scalable Data Validation

Reusable ETL Test Assets

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Integration with Test Management tools

Sync reusable test assets with platforms like ADO test plans or TestRail to standardize QA and publish results of Data Validation runs directly to tools like JIRA for consistent cross-team reporting

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ETL & ELT Testing

Scale Data Validation across ETL and ELT architectures with reusable logic. Ensure consistency across cloud platforms without duplicating effort.

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Extensibility

Extend your workflows for data extraction, enrichment, and file operations. Integrate with external systems to bridge the gap between ETL testing and your broader tech stack.

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Reusable ETL Test Assets

Operationalize ETL Testing

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Pipelines & Scheduling

Schedule data validation runs and chain test plans for repeatable checks so issues surface early, not after release.

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DevOps & CI/CD Integration

Trigger ETL validation workflows directly from CI/CD to integrate testing into DevOps deployments and ensure zero-defect data pipelines.

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Audit Trail & Reporting

Track recent runs and export reports to speed reviews, approvals, and root-cause analysis to improve cross team collaboration

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Operationalize ETL Testing

Agentic AI — Built Into ETL Validator

AI agents handle the repetitive work so your engineers focus on real business problems.

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Accelerated Test Authoring

AI generates test cases from mapping docs, SQL prompts, or schema metadata — test creation goes from days to minutes.

All-in-one AI for data validation

Self-Healing Test Scripts

When schemas change, validation rules update automatically — zero manual rework when pipelines evolve.

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Instant Root-Cause Analysis

AI explains every discrepancy in plain language: column, error type, affected record count. No investigation required.

Every Data Validation Scenario — Proven Across Industries

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

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Banking & Financial Services

Validate mainframe-to-cloud migrations and SOX/BCBS-239 pipelines — 100% coverage, audit-ready evidence on every run.

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Healthcare & Life Sciences

Validate HL7/FHIR pipelines and HIPAA-governed patient record transformations — every field verified, zero PHI exposure in testing.

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Consumer Packaged Goods

Reconcile Nielsen/IRI syndicated data and high-volume Oracle/SAP-to-Snowflake migrations. Bad demand data costs shelf space.

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Higher Education & Research

Validate student records, financial aid pipelines, and federal compliance data. One missing record in an audit is a compliance event.

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Hospitality

Validate reservation, loyalty, and revenue pipelines before data reaches yield models. Wrong inputs in pricing cost real revenue.

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Retail

Validate 50+ source systems into unified commerce platforms. One bad UPC mapping corrupts a week of sales data across every channel.

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

Featured Customer Story

CPG Leader — Oracle to Snowflake Migration With Zero Data Loss

A Data warehouse migration with thousands of tables and no room for error in production reporting.

The Challenge

Validate millions of records across legacy and cloud systems before business teams flipped over.

What Datagaps Delivered

End-to-end automated migration validation with continuous production monitoring.

The Outcome

Went live on schedule with full data parity and continuous production monitoring in place.

100%

Record-level validation coverage

70%

QA cycle time reduction

80%

Faster BI regression testing

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Post-go-live data defects

ETL Validator vs. The Alternatives

See exactly how ETL Validator compares to manual scripting and generic test tools across the capabilities that matter.

Technical CapabilityDatagaps ETL ValidatorAlternative ETL testing toolsCustom Built Tool from LLM
Data coverage 100% full-volume ~ Often sample-based ~ Only what you build
Test authoring AI agents from mapping, SQL, ETL code Manual / scripted Hand-coded + prompt work
Schema-change maintenance Self-healing Manual rework Breaks on drift; constant upkeep
Connectors 200+ built-in ~ Varies Build & maintain each
Time to value Days ~ Weeks Months
Upfront investment Subscription, no build ~ License High eng build + infra
Expertise required Low-code for all ~ Tool-specific Expert Resource needed
CI/CD + audit-ready evidence Native ~ Varies Build it yourself
Compliance Audit ready, Industry specific ~ Varies Difficult to Comply
Ongoing cost & risk Vendor-maintained & supported ~ Vendor-dependent 10-40 eng hrs/mo • key-person risk

Trusted by Data Teams Worldwide

See how leading companies are transforming their data operations with Datagaps

Data Integrity and The Human Element

“With Datagaps, we saw about 70% time savings, an 80% reduction in turnaround time and 100% adherence to our UI validation best practices.”

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Biswadeep Ghosh

Principal/Partner
ZS

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Data Intzegrity and The Human Element

“ETL Validator has really freed the IT department to look at real business problems and not worry about the trust and veracity of the data… “

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Ajit Oak

Head of Business
Intelligence

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Data Intzegrity and The Human Element

“With Datagaps, we moved from reactive data correction to proactive data governance, with audit-ready reports available for our leadership and ETL teams.”

Sreelatha Nair

Sreelatha Nair

Project Lead, New York
University United States

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Get Started Today

See ETL Validator in Action

Reduce your data testing costs dramatically with ETL Validator- Get your 14 days free trial now.
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SOC 2 Type II certified | ISO 27001 certified | No credit card required for trial | Your data never leaves your environment

ETL is where data trust begins. DataOps Suite is where it's complete.

ETL Validator is one product within DataOps Suite — Datagaps’ unified platform that extends automated testing from your pipelines to your reports, your data quality, and beyond.

Ingestion stage, validated by Datagaps ETL Validator

Ingestion

ETL Validator

ETL/ELT stage, validated by Datagaps ETL Validator

ETL / ELT

ETL Validator

Data Quality stage, monitored by Datagaps DQ Monitor

Data Quality

DQ Monitor

BI Dashboards stage, validated by Datagaps BI Validator

BI Dashboards

BI Validator

AI/ML stage, powered by Datagaps DQ Monitor and TDM

AI / ML

DQ Monitor + TDM

Datagaps DataOps Suite - Intelligent Data Validation Platform with Agentic Al

DataOps Suite

Intelligent Data Validation Platform
with Agentic Al

Learn more about DataOps Suite
ETL Validator - Automated data validation and ETL testing with agentic AI

ETL Validator

Automated data validation and ETL testing with agentic AI.

Learn more about ETL Validator
BI Validator - Smarter BI validation for Power BI, Tableau and Oracle Analytics

BI Validator

Smarter BI validation for Power BI, Tableau and Oracle Analytics.

Learn more about BI Validator
Data Quality Monitor - Proactive data quality with agentic AI predict, prevent, govern

Data Quality Monitor

Proactive data quality with agentic AI predict, prevent, govern.

Learn more about DQ Monitor
Test Data Manager - Compliant, realistic synthetic test data, enabled by agentic AI

Test Data Manager

Compliant, realistic synthetic test data, enabled by agentic AI.

Learn more about TDM

FAQ's about ETL Validator

 Common questions from Enterprise Buyers

How does ETL Validator achieve 100% row-level validation?

The US-patented Extract-Load-Validate architecture runs comparison SQL natively inside your Snowflake, Databricks, or Oracle environment — every record validated using your own compute. Zero data leaves your infrastructure. See how ETL Validator works.

What ETL validation checks does it run?

Nine categories: row count, data content, schema/type, transformation logic, referential integrity, null handling, aggregation, duplicate detection, and SCD Type 2. Each produces a row-level exception report with AI root-cause explanation. See full ETL testing guide → 

Does it integrate with our CI/CD pipeline?

Yes — native integrations with Azure DevOps, GitHub Actions, GitLab, and Jenkins via the DataOps CLI. Validation runs automatically on each deployment; pass/fail gates block bad data from reaching production. Explore the DataOps Suite → 

Can it automate data migration testing?

Yes. ETL Validator validates 100% of records across Oracle-to-Snowflake, SAP-to-Databricks, and mainframe-to-cloud migrations — with mapping spec import, cutover-window testing, and audit-ready reports. Explore data migration testing → 

How does Agentic AI reduce manual effort?

AI reads your mapping document or schema metadata and auto-generates every test case. Handles schema drift with self-healing tests — zero manual rework when pipelines change. Watch a 3-min demo → 

What ROI can I expect?

Enterprise teams report 60–70% reduction in ETL testing time, 70% QA cost savings, and up to 35% faster migration delivery. Calculate your ROI → , Read case studies → 

Is my data secure during validation?

Comparison SQL runs inside your own environment — no data sent to external AI services. SOC 2 Type II and ISO 27001 certified. The embedded LLM runs locally. View compliance details → 

Can I use ETL Validator with the full DataOps Suite?

Yes. Available standalone or as part of the DataOps Suite — with BI Validator, Data Quality Monitor, and Test Data Manager on one shared platform with unified lineage and one audit trail.

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