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DataOps Suite
The complete platform
Data Quality Monitor
Continuous quality monitoring
ETL Validator
ETL, ELT and migration testing
BI Validator
Dashboard and report testing
Test Data Manager
Compliant synthetic test data
Platform Overview
See how it works

DataOps Suite

Data Quality and Agentic AI platform that validates, reconciles, scores, monitors and remediates data from ingestion to BI and AI.

Why one platform

Agentic AI-powered test and rule creation
Agents generate data quality rules, validation tests and SQL from prompts, with your approval.
Data quality score per dataset
Shows the current score, what changed since the last run and the failing records behind it.
Validation and observability inside the pipeline
Every load is compared with its source, transformations are tested against business logic, and freshness, volume and schema changes are monitored.
Reports that match the source
Dashboard figures are compared with the source data behind them before users see them.
Test data without real records
Synthetic data that mirrors production replaces sensitive records in test environments.
Quality gates for releases
Pipeline and report changes are tested before they go to production.
Explore DataOps Suite Platform

Data Quality Monitor

Continuously profiles, validates and scores enterprise data, with Agentic AI that recommends rules and flags anomalies, so analytics and AI run on trusted data.

Capabilities

AI-recommended DQ rules and scoring
Agents suggest completeness, validity and uniqueness rules, with scores down to the column.
Data profiling
Analyzes distributions, patterns and frequencies to surface outliers.
AI-based observability
Agents monitor pipelines end to end, detect anomalies and suggest fixes.
Data catalog
Organizes models and tables in one catalog, with AI-drafted descriptions.
Data lineage
Traces data from origin to destination through every transformation.
Data quality issue tracking
Assigns every failing record to an owner and tracks it to resolution.
Explore Data Quality Monitor

ETL Validator

Automates ETL/ELT testing, with Agentic AI that builds tests from mapping docs, confirming every record arrives complete, accurate and correctly transformed.

Capabilities

AI-generated ETL tests
Turns mapping docs into checks for joins, transforms and edge cases.
Source-to-target validation
Matches loaded data to the source, down to record counts and required fields.
Transformation validation
Verifies business logic with SQL, Python or Scala.
Migration validation
Checks schema, row counts and integrity for cloud migrations.
Metadata change audit
Catches schema and metadata discrepancies before they break pipelines.
Root cause and adaptive tests
Pinpoints where data broke, and agents update tests when mappings change.
Explore ETL Validator

BI Validator

Automates testing and governance for Power BI, Tableau and Oracle Analytics, with Agentic AI that builds tests from plain English and keeps reports accurate and reliable.

Capabilities

AI-created BI tests
Describe a test scenario in plain English, and agents build it.
Visual-to-source comparison
Compares the data behind every visual to the source using auto-generated SQL.
Regression and upgrade checks
Pixel-level comparisons across environments, with AI summaries of what changed.
Measure logic checks
Converts BI measures and calculations to SQL to confirm KPI logic.
Performance and load testing
Simulates concurrent users and measures load and refresh times.
BI governance
Finds unused measures, duplicate reports and orphaned tables.
Explore BI Validator

Test Data Manager

Uses Agentic AI to detect and mask sensitive data and generate synthetic data that mirrors production, so teams can test without exposing real records.

Capabilities

AI synthetic data generation
Learns patterns from a small sample to create production-like data.
PII discovery and masking
Detects PII and PHI and replaces it with realistic fake values.
Relationship-aware data
Keeps linked tables connected with referential integrity.
Millions of records in minutes
Scales for load, stress and performance testing.
Multi-format output
CSV, Parquet or JSON, or loaded straight into test databases.
Compliant by design
Cloud or on-prem, supporting GDPR and HIPAA requirements.
Explore Test Data Manager
Data Quality Use Case
The problem to solve
Cloud platforms
Warehouses, lakes and CRM
BI and analytics
Dashboards and reports
ROI calculator
Estimate the time and cost you’ll save.

Data Quality Use Case

Start from the outcome your team needs, with Agentic AI doing the groundwork.

Data Migration Testing
Proves data moved intact from legacy and on-prem systems to new platforms through cutover.
Data Reconciliation
Finds missing, mismatched, orphan and duplicate rows between source and target.
Data Observability
Tracks freshness, volume and schema changes across pipelines, with AI agents tracing root causes.
Data Remediation
Routes failing records to owners, suggests fixes and tracks each one to resolution.
Data Compliance
Audit-ready evidence for SOX, HIPAA, GDPR, CCPA, FERPA, NAIC and MAR.
AI Ready Data
Validates the data feeding ML models and catches drift before retraining.

Cloud Platforms Use Case

Validate and monitor data and its quality on the platforms you already run, backed by Agentic AI.

Snowflake
Validates and scores data inside Snowflake with SQL pushdown, catching schema drift and migration gaps.
Databricks
Validates Delta Lake tables from Bronze to Gold inside notebooks, with results in Unity Catalog.
Microsoft Fabric
Validates Fabric data from OneLake ingestion through Lakehouse and Warehouse to Power BI semantic models.
Azure Synapse
Validates Synapse migrations and Medallion-layer transformations, with tests running in Azure DevOps.
Salesforce
Checks Salesforce objects, uploads and updates for completeness and quality on every migration and ingest.

BI and Analytics Use Case

Keep every report accurate across your BI tools, as Agentic AI builds the tests for you.

Power BI
Matches visuals to source data and tests DAX, slicers and row-level security from Dev to Prod.
Tableau
Matches dashboards to source tables, checks calculated fields and row-level security, and catches drift across versions.
Oracle Analytics
Matches analyses to SQL results, tests subject areas and permissions, and validates OBIEE to OAC migrations.
Financial services
SOX, BCBS 239 and NAIC MAR
Healthcare
HIPAA, EHR migration and APCD
Life sciences
GxP and 21 CFR Part 11
Manufacturing
ERP migration and supplier data
Retail and utilities
Settlement, pricing and NERC CIP
Higher education
FERPA, IPEDS and research data

Banking, Financial Services, and Insurance (BFSI)

Stop reporting errors before examiners find them, with every number traced from core system to board dashboard.

How Datagaps helps

Core platform migrations
Cut over banking and insurance platforms, including mainframe to cloud, without losing a record.
Regulatory reporting
Hold submissions until the data meets quality thresholds.
Financial reconciliation
Match GL to subledger automatically, with every break flagged.
Risk and credit data
Catch drift before risk, lending and pricing models degrade.
Dashboard attestation
Prove capital and board dashboards match the warehouse.
See How it Works

Healthcare

Keep claims and clinical data accurate through every migration, without exposing patient records in testing.

How Datagaps helps

EHR migrations
Confirm every record survives the move to Epic, Cerner or Oracle Health.
Claims data quality
Catch errors in claims and remittance feeds as they arrive.
APCD submissions
Check every file against state templates before you submit.
Clinical dashboards
Catch KPI and report changes after every refresh.
Provider directories
Keep provider listings accurate, current and audit-ready.
See How it Works

Life Sciences

Catch issues in clinical and real-world data before submission, and keep trial subject data out of test environments.

How Datagaps helps

Clinical data migrations
Move EDC, CTMS and LIMS data to the cloud without losses.
CRM migrations
Keep rebate calculations right through Veeva and Salesforce moves.
Pharmacovigilance data
Catch adverse event data issues before regulatory submission.
Commercial and clinical dashboards
Trace every KPI back to source clinical and lab records.
De-identified trial data
Keep subject data out of test, analytics and AI environments.
See How it Works

Manufacturing

Avoid broken ERP cutovers and supplier overpayments, and catch sensor drift before it hits production.

How Datagaps helps

ERP migrations
Move BOM, inventory and financial data across Oracle, SAP and cloud without breaks.
Supplier reconciliation
Catch overpayments and duplicate invoices with three-way PO, ASN and invoice matching.
Sensor data quality
Catch drift before it skews predictive maintenance and yield models.
Operations dashboards
Catch report breaks after every release or upgrade.
Safe ERP test data
Keep supplier pricing and production volumes out of lower environments.
See How it Works

Retail and Utilities

Catch settlement, inventory and pricing errors before your customers or regulators do.

How Datagaps helps

Settlement reconciliation
Match marketplace payout files to the general ledger, record by record.
Inventory accuracy
Keep POS, ERP and warehouse numbers in sync.
Pricing and promotions
Catch price and promotion mismatches across channels.
Reliability dashboards
Keep SAIDI and SAIFI reliability reporting accurate.
BI under load
Make sure reports hold up for thousands of concurrent users.
See How it Works

Higher Education & Research

Get enrollment, financial-aid and transcript data right before SIS cutover, before students feel it.

How Datagaps helps

SIS migrations
Validate moves from Banner or PeopleSoft to Workday Student or Ellucian.
Financial-aid reconciliation
Match aid and Bursar data to the general ledger.
Enrollment reporting
Keep census and admissions dashboards consistent from cycle to cycle.
Federal reporting
Monitor data quality ahead of IPEDS submissions.
Safe student data
Test and train AI without exposing real student records.
See How it Works

Trusted Data Summit

A practitioner summit focused on the validation, observability, governance, and reconciliation practices that determine whether enterprise data is ready for AI.

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Nov 19th, 2026
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Datagaps works natively with the cloud, data and BI platforms your teams already run.

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Solutions

Use cases

Data migration testing
Proves data moved intact from legacy and on-prem systems to new platforms through cutover.
Data reconciliation
Finds missing, mismatched, orphan and duplicate rows between source and target.
Data observability
Tracks freshness, volume and schema changes across pipelines, with AI agents tracing root causes.
Data remediation
Routes failing records to owners, suggests fixes and tracks each one to resolution.
Data Compliance
Audit-ready evidence for SOX, HIPAA, GDPR, CCPA, FERPA, NAIC and MAR.
AI Ready Data
Validates the data feeding ML models and catches drift before retraining.

Cloud platforms

Snowflake
Validates and scores data inside Snowflake with SQL pushdown, catching schema drift and migration gaps.
Databricks
Validates Delta Lake tables from Bronze to Gold inside notebooks, with results in Unity Catalog.
Microsoft Fabric
Validates Fabric data from OneLake ingestion through Lakehouse and Warehouse to Power BI semantic models.
Azure Synapse
Validates Synapse migrations and Medallion-layer transformations, with tests running in Azure DevOps.
Salesforce
Checks Salesforce objects, uploads and updates for completeness and quality on every migration and ingest.

BI and analytics

Power BI
Matches visuals to source data and tests DAX, slicers and row-level security from Dev to Prod.
Tableau
Matches dashboards to source tables, checks calculated fields and row-level security, and catches drift across versions.
Oracle Analytics
Matches analyses to SQL results, tests subject areas and permissions, and validates OBIEE to OAC migrations.

ROI calculator →

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Azure Synapse Testing Automation

DataOps suite enables users to perform end-to-end  testing automation of Azure Synapse projects

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Microsoft Azure Synpase Analytics

Benefits of Automating Azure Synapse Testing

Automating Azure Synapse testing streamlines data quality verification, enhances operational efficiency, and reduces the risk of errors in data warehousing processes.

Improve Reliability of data in Azure Synapse

Bloor states that 64% of data migration issues arise from inadequate data mapping

Reduce Cost of Migration to Azure Synapse

Gartner reports that 83% of data migration projects fail or exceed budgets and schedules.

$

Empower users to make better decisions

Bloor Group reports that more than 80% of data migration projects run over time or over budget

Key Features

Automate Testing of Data Migration to Azure Synapse

Validate Schema Conversion to Azure Synapse

Ensure that the Data Mapping is correct and validate Schema conversion prior to migrating data to Azure Synapse.

Test Data Integrity and Completeness after Data Migration

Verify that all required data has been migrated by comparing data counts, data profiles & records between the Source and Azure Synapse.

Regression and Stress Test Reports on Azure Synapse

Compare the functionality and performance of reports pre and post migration to ensure that the expectations are being met.

Automating Test of Data Migration to Azure Synapse
Azure Synapse ELT Testing Automation

Automate Azure Synapse ELT Testing

Automate Azure Synapse Transformation Testing

Ensure that the Azure Synapse ETL and ELT pipelines are working as expected by automating the Transformation testing between different layers of your Medallion Architecture.

Test Data Ingestion to Azure Synapse

Ensure data ingested into Azure Synapse is meeting the Data Quality requirements and verify that the data is consistent with source data.

Automate Azure Synapse Data Quality Testing

Automate Data Validation in Azure Synapse by measuring Data Quality using a combination of Data Quality rules and Data Observability.

Automate Azure Synapse Report Testing

Functional Testing of Reports on Azure Synapse

Build trust in reports built on Azure Synapse by comparing the data in the reports (eg. Power BI, Tableau) with data in Azure Synapse

Azure Synapse Performance Testing

Simulate concurrent user load to test performance of the reports and Azure Synapse Data Warehouse ensuring that the SLAs are being met

End-to-end testing of Azure Synapse

Perform end-to-end testing of Azure Synapse Data Warehouse from the point of ingestion to the point of consumption

Azure Synapse Report Testing Automation
Integrate with Azure DevOps & Azure Testing Plans

Integrate with Azure DevOps & Azure Test Plans

Run tests in Azure DevOps (ADO) Pipeline

Use custom ADO task to automatically trigger execution of tests in Azure Synapse Data Warehouse.

Integrate with Azure Test Plans

Map Azure Test Plans with automation tests in DataOps suite. Execute tests in DataOps suite and report test results in Azure Test Plans

Store Automation Tests in Azure Repos

Save automation tests from DataOps suite in Azure Repos enabling CI/CD integration

Case Studies

Our clients receive great value from our data validation solutions

Applications to the Cloud

Modernizing Court Systems: Automating Data Migration and Validation

Download Case Study
Marketing and Commerce data

Transforming Data Quality for Ad Optimization & Marketing Analytics

Download Case Study
Case Study Image for Global-Research-Firm-Enhances-Data-Validation-with-Datagaps-DataOps-Suite

Global Research Firm Enhances Data Validation with DataOps Suite

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iCEDQ Alternative
Datagaps vs iCEDQ: An Honest Guide to End-to-End Data Quality & Validation

Datagaps vs iCEDQ: An Honest Guide to End-to-End Data Quality & Validation

best 3 etl testing tools
Top 3 ETL Testing Tools

Top 3 ETL Testing Tools

Datagaps vs QuerySurge An Honest Buyer's Guide to Enterprise Data Validation
Datagaps vs QuerySurge: A Buyer’s Guide to Data Validation

Datagaps vs QuerySurge: A Buyer’s Guide to Data Validation

Automate Power BI Testing using BI Validator
DataOps TDM Webinar
Automate Power BI Testing using BI Validator

ETL Validator – 14 days free trial in our sandbox

Automate data warehousing, data migration and big data testing projects.

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Data Quality Monitor

Continuously assess, score, and improve your enterprise data quality using rule-based and AI-powered validation
Automated Data Quality Checks at Scale

Validate uniqueness, completeness, domain accuracy, and detect orphan records.

AI-Driven Anomaly Detection and Alerts

Identify data drift and outliers using ML-based statistical methods and IQR-based profiling.

Low-Code Rule Configuration with Data Rule Wizard

Create and deploy validation rules quickly without coding, even across large datasets.

Graphical Scoring and Monitoring Dashboard

Visualize data quality trends across models, tables, and records with actionable insights.

CI/CD and Cloud Integration Ready

Enable continuous validation across pipelines using integrated APIs and DevOps compatibility.

Test Data Manager

Generate high-quality synthetic test data securely while maintaining regulatory compliance with HIPAA, GDPR, and CCPA
AI-Powered Synthetic Test Data Generation

Automatically create realistic data based on patterns in production while masking PII/PHI.

Reduced Cost and Time for Test Data Preparation

Eliminate manual rule-writing and speed up test readiness for complex use cases.

Support for Diverse Data Formats and Models

Generate millions of records in JSON, XML, CSV, relational, or hierarchical formats.

Secure, Policy-Driven Data Masking

Ensure sensitive fields are protected using deterministic, reversible, or random masking.

Flexible Deployment Across Cloud or On-Prem

Deploy within your secure environment and integrate into automated pipelines seamlessly.

ETL Testing

Maximize the efficiency, quality, and reliability of your data pipelines through intelligent automation, validation, and scalability.
100% Data Validation Across Pipelines

Validate billions of records using Spark-powered parallel execution across on-prem and cloud sources.

Accelerated Migration and QA Cycles

Reduce migration testing time by up to 60% and QA costs by 30% with automated workflows.

Automated Metadata and Transformation Testing

Detect schema mismatches and ensure business rules are correctly applied via AI-assisted validation.

Seamless Collaboration and Governance

Enable role-based access, ALM integration, and shareable web reports to unify cross-team efforts.

Low-Code/No-Code Test Creation with AI

Empower both technical and business users to build, schedule, and execute validations using prompt-based automation.

BI Validator

Ensure accuracy, performance, and security of your Business Intelligence dashboards and reports across platforms like Tableau, Power BI, and Oracle Analytics
Automated Regression Testing Across BI Reports

Detect broken visuals or logic changes post-upgrade and data refreshes.

Cross-Platform Validation of Reports and Dashboards

Compare visuals and data across environments and BI tools with zero manual effort.

Performance and Load Testing for BI Assets

Simulate concurrent user access to measure response times and report load failures.

Access and Security Validation

Ensure only authorized groups have access to the correct records and reports.

Aesthetic and Metadata Change Detection

Identify formatting inconsistencies, filter changes, and layout drift with each release.

Products

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DataOps Suite

Intelligent Data Validation and Analytics Testing Platform with Agentic AI.

ETL Validator automated ETL testing tool

ETL Validator

Automated Data Validation and ETL Testing with Agentic AI.

BI Validator automated BI testing tool

BI Validator

Smarter BI Validation For Power BI, Tableau, Oracle Analytics – Accelerated by AI Agents.

Data Quality Monitor software

DQ Monitor

Proactive Data Quality with Agentic AI – Predict, Prevent, Govern.

Test Data Manager software

Test Data Manager

Generate compliant and realistic test data for all your testing needs, enabled by Agentic AI.

Solutions

Use Case

AI-Ready Data
Data Migration Testing
Data Observability
Data Reconciliation
Data Remediation
Compliance
APCD Solutions

Cloud

Snowflake
Databricks
Azure Synapse
Salesforce
Microsoft Fabric
APCD Solutions

Analytics

Power BI
Tableau
Oracle Analytics

Industry

Healthcare
BFSI
Life Sciences
Retail & Utilities
Manufacturing
Higher Education
Compliance Solutions
Datagaps DataOps Data Observability Tool

Data Observability

Data Reconciliation tool

Data Reconciliation

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