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Intelligent Data Validation and Analytics Testing Platform with Agentic AI

Unified Data Pipeline & BI Test Automation Powered by Agentic AI for Adaptive Reconciliation, Continuous Validation and Reliable Insights.

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One Platform Many Capabilities

One Platform - DataOps Suite
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The Comprehensive End-to-End Data Validation Platform, Now Powered by Agentic AI for Autonomous Data Quality and Testing.

ETL Validator

BI Validator

Data Quality Monitor

TDM

Automated Data Validation and ETL Testing with Agentic AI.
 
ETL Validator is a low-code platform for automated ETL/ELT testing, ensuring accurate, trustworthy data across cloud and on-prem pipelines for faster, reliable delivery.

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Smarter BI Validation For Power BI, Tableau, Oracle Analytics – Accelerated by AI Agents.
 
BI Validator is a no-code BI testing tool that automates validation of dashboards, data, and performance - ensuring integrity, consistency, and trust across analytics environments.

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Proactive Data Quality with Agentic AI – Predict, Prevent, Govern.
 
Data Quality Monitor ensures complete, accurate, and trusted data with AI-powered validation, observability, profiling, and reconciliation across all stages of your data pipeline.

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Generate compliant and realistic test data for all your testing needs, enabled by Agentic AI.
 
Test Data Manager uses AI to generate high-quality, privacy-safe synthetic data, enabling realistic, scalable testing of applications, pipelines, and analytics without exposing sensitive information.

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End to End Data Testing Automation

End to End Data testing Automations

DataOps Suite Battle-Tested Proven Records

$5.3M

Savings Annually

5000+

Test Cases Run Daily

1000+

Rules per Data Model

100

Unique Instances

10B+

SAP Records Processed

70%

Improved Productivity

35%

Reduce Project Timeline

200%

Increase Test Coverage

KEY FEATURES

Let’s Find and Fix it Together

ETL Validator is a powerful ETL/ELT testing tool that automates validation during data migration and data warehouse projects.

  • No-code ETL transformation testing
  • AI-powered Data Quality assessment
  • Visual Test Case Builder
  • DB Metadata Testing
  • AI-powered Faster Test Authoring

Streamline and enhance the testing of BI reports, ensuring data accuracy and reliability across BI platforms.

  • Automated Testing of Upgrades & Migrations
  • Performance & Stress testing of BI Reports
  • Easy Wizard-Based Test Creation
  • Enables Continuous Integration For BI
  • AI Agent-driven Proactive Defect Prevention

DataOps DQ Monitor automates data testing in motion and at rest, allowing users to monitor data quality metrics via intuitive dashboards.

  • Data Quality Dashboard
  • Data Quality Score
  • DQ Dimensions
  • Data Reconciliation
  • AI-powered Anomaly Detection
Easily create synthetic test data with Datagaps. A small sample size generates variations for your AI/ML. 
  • Stay GDPR Compliant
  • Dynamic Data Masking
  • Stress Tests Your Data Pipeline to Handle High Throughputs in Production
  • Blackbox Testing With Variants Tuning Before Test Data Generation
  • AI Agent Enabled Privacy-Aware Testing
ETL Validator Key features
BI Validator Key features
Data Quality Monitor Key Features
Test Data Manager Key features

DIFFERENTIATORS

What makes Datagaps DataOps Suite Unique?

Automates Data Quality Monitoring, Observability, and Reconciliation from ingestion to AI/analytics. Also automates ETL & BI testing for varied use cases.
 
Comprehensive Automation
All-in-One DataOps Suite
Eliminates the need for multiple tools by integrating all capabilities into a single platform, reducing complexity and cost.
 
Extensibility & Customization
Supports custom plugins to extend product functionality and reuse assets. Allows users to create custom integrations and features.
 
Enterprise-Grade Integrations
Integrates with Collibra, Azure DevOps, GitHub, Jenkins, etc., for seamless CI/CD and version control.
 
Scalability via Spark-Based Architecture
Handles high-volume data and supports parallel test execution. API-enabled test case creation ensures large-scale automation.
 
Reusability & Efficiency
Test cases, rule sets, and templates are reusable across projects and environments. Parameterized test cases enable cross-environment execution.
 
Built-in GenAI Capabilities
Embedded LLM ensures data security (no external sharing). Automates test and rule creation, requiring minimal human effort.
 
Ease of Use
Drag-and-drop interface with minimal coding required. Usable by anyone with basic SQL knowledge after short training.
 
Agnostic Deployment & Compliance
Deployable on any cloud, on-premise, or hybrid setup. Fully compliant with healthcare, finance, insurance, and federal regulations.
 
Exceptional Support & Customer Success
Strong customer support and dedicated teams ensure seamless adoption. Customers praise its broad applicability across use cases.

Awards & Recognition

patented technology

US Patent US 201220290527- Data extraction & testing methods ELV Architecture

Big data campiness award datagaps

Top 100 Most Promising Big Data Companies CIO Review Special Edition

informatica seal - datagaps

Datagaps ETL Validator Earned informatica’s
Seal of approval

SOC 2 cerificate

Globally recognized auditing for security integrity, confidentiality and privacy standards

Everything Data

Industries we make impact

  • Banking and Finance
  • Retail/E-commerce
  • Healthcare
  • Pharma & Life Science
  • Higher Education
  • Government & Public Sector

IDEAL FOR THESE ROLES

  • Chief Data Officer
  • Data Scientists
  • Business Intelligence Analysts
  • BI Developers
  • ETL Developers
  • Compliance Officers
  • Data Quality Managers
  • Data Governance Managers
  • QA Leads, Architects & Analysts
  • Data Analysts
  • Data Management Heads
  • Data Warehouse Managers/Architects

Analytics Ops

Analytics FinOps

Data GovOps

Integrate Your Tech Stack Effortlessly

Plug and Play Connectivity with your DevOps stack

dataops suite stack integration

USE CASES

Eliminate Blind Spots and Release with Confidence​

Data Validation Across Pipelines

Validate data continuously across pipeline stages to catch errors early and support real-time monitoring.

Enable trusted decisions with automated checks during pre- and post-transformation phases.

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Data Migration Testing

Ensure consistency with schema and row-level comparisons, plus real-time monitoring during migration.

Minimize downtime, prevent data loss, and support smooth transitions across environments.

BI Dashboard Regression Testing

Detect data or visual mismatches and perform regression testing to validate dashboards after changes.

Ensure reports remain accurate post-updates, preserving stakeholder confidence in analytics.

Data Quality Monitoring

Apply automated rules and continuous monitoring to catch nulls, schema drift, and data anomalies.

Proactively validate data to ensure reliability before users access it.

Automate ETL run validation and use repeatable tests to catch transformation issues.

Maintain reliable, accurate data flows while reducing manual effort and debugging time.

ETL Process Validation

Simulate high-traffic loads and test scalability across ETL jobs and dashboards.

Identify bottlenecks early to prevent failures and ensure optimal performance under stress.

Performance and Load Testing

Monitor data flow and patterns continuously using ML to detect real-time anomalies and find root causes.

Improve trust and reliability with faster issue resolution and proactive data management.

Data Observability

Compliance and Regulatory Reporting

Log validations for traceability and generate transparent, audit-ready reports aligned with industry standards.

Reduce compliance risk and stay prepared for audits with complete, verifiable documentation.

Embed automated data validations into CI/CD workflows to detect issues early and streamline deployments.

Run tests with every release to boost confidence, reduce errors, and improve production data quality.

Pipeline Integration

Automated Test Case Creation

Auto-generate test cases across pipelines, migrations, and dashboards to expand coverage with less effort.

Reduce manual errors and save time by supporting multiple testing platforms and frameworks.

Our Customers Speak

Kasturi Sen NYU, Data Governance Lead
NYU

NYU Review on Datagaps DQ Monitor

❝ Datagaps is a great partner. I love working with them, and we’re excited to incorporate their AI-driven data quality capabilities, so we don’t fall behind.❞

— Kasturi Sen

Senior Data Warehouse Architect, New York University
Video
“ The ETL validator tool provides an intuitive interface and a strong Datagaps partnership. It ensures 100% data validation, cost-effectiveness, and boosts productivity with responsive support. “
Michael Lucas
Michael LucasApplications Programmer 3 - CNPRC
“ Building strong customer relationship and implementing innovative solutions is the core value we follow. Here’s what our customers around the global think of Datagaps.handouts.“
Ajit Oak
Ajit OakDirector, Head of Business Intelligence - Broadcom
“ The ETL validator tool provides an intuitive interface and a strong Datagaps partnership. It ensures 100% data validation, cost-effectiveness, and boosts productivity with responsive support. “
Michael Lucas
Michael LucasApplications Programmer 3 - CNPRC
“ Building strong customer relationship and implementing innovative solutions is the core value we follow. Here’s what our customers around the global think of Datagaps.handouts.“
Ajit Oak
Ajit OakDirector, Head of Business Intelligence - Broadcom

Resources

14 Days Free Trial

Datasheet

Use Cases

Documentation

FAQs

Support

FAQ's

What is Datagaps DataOps Suite?

Datagaps DataOps Suite is an end-to-end data validation platform that automates testing across ETL, BI, data quality monitoring, and test data generation.

How is DataOps Suite different from ETL Validator?

ETL Validator focuses on ETL testing, while DataOps Suite includes ETL Validator plus BI Validator, Data Quality Monitor, and Test Data Manager for complete data lifecycle validation.

What modules are included?

DataOps Suite includes ETL Validator, BI Validator, Data Quality Monitor, and Test Data Manager.

Which environments does DataOps Suite support?

DataOps Suite supports on-premises and cloud databases, multiple file formats (CSV, JSON, XML, Parquet), and big data platforms like Azure, Databricks and Snowflake.

Does it integrate with CI/CD workflows?

Yes, DataOps Suite integrates with CI/CD tools like Jenkins and GitHub for automated testing in pipelines.

Is Agentic AI secure?

Yes, Agentic AI runs internally without sharing data externally, ensuring security.

What does “Agentic AI” do here beyond standard automation?

Agentic AI accelerates auto‑authoring of SQL/tests from natural language, enriches metadata (auto descriptions), maintains tests under schema drift, and suggests context‑aware data quality rules. In BI validation, it can summarize report differences and generate test suites; in ETL, it can infer mappings from SQL/stored procedures.

Who should use DataOps Suite?

Ideal for BI analysts, data quality engineers, testers, architects, and data governance teams.

What deployment options are available?

Supports on-prem, cloud, and hybrid deployments on Windows and Linux environments.

Is the platform scalable?

Yes, it uses Apache Spark for high-volume data and parallel test execution.

What are common use cases?

Pipeline validation, data migration testing, BI regression testing, real-time monitoring, and compliance reporting.

Is there a free trial?

Yes, you can start a free trial or request a demo from the product page.

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