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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.

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.

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.

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.

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.
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 youโ€™ll save.
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.

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.

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.

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.

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.

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.

Trusted Data Summit

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

Save Your Spot
Nov 19th, 2026
Technology Partners
Cloud, data and BI platforms
SI Partners
Consulting and implementation

Become a partner

Resell, implement or co-deliver

Technology Partners

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

Our technology partners

SI Partners

Consulting and integration firms that deliver Datagaps validation for enterprise clients worldwide.

Our SI partners

Solutions

Use cases

Cloud platforms

BI and analytics

APCD Compliance Made Simple and Accurate

Ensure seamless compliance with All-Payer Claims Database (APCD) reporting requirements through automated validation, data quality checks, and secure data handling.
APCD Compliance Solutions

Why APCD Compliance Requires Modern Automation

APCD reporting involves strict state-specific rules, and manual processes often cause delays and errors. Automation delivers faster, more accurate, and easier compliance.

Benefits

Streamlined APCD Compliance Through Automation and Integration

Pre-built Rulesets for Each State

Custom solutions that align with individual state requirements to ensure compliance.

Automated Data Validation

From data type checks to completeness thresholds, automate every aspect of APCD submissions.

Low-Code Integration

Seamlessly integrates into existing pipelines, enhancing them without disruption.

Key Features

Key Features of APCD Compliance Automation

Unified Automation in APCD Compliance

Unified Automation for APCD Compliance

State-Specific Templates

Ensures each submission adheres to state standards.

Alerts and Reporting

Monitors submissions and flags issues as they arise, with automated alerts and notifications for quick resolution.

Automated Rule Application

Implements over 150 rules per file to maintain stringent data quality.

End-to-End Encryption and Data Handling

Safeguards sensitive information in transit and at rest.

Additional APCD-Focused Capabilities

End to End Data Testing

Source to โ†”target comparisons across heterogeneous platforms with every reported output linked back to origin.

Data Reconciliation

Matches data across systems to confirm consistency and trace outputs back to original sources.

Flat File Testing (with file watcher)

Auto detects new incoming files and kicks off tests immediately resulting in event driven, continuous control.

Identify differences between Report & SQL output

Ties report โ€œactualsโ€ directly to source of truth SQL โ€œexpected,โ€ providing a defensible linkage from output back to source data

Additional APCD-Focused Capabilities

Case Study

Our clients receive great value from our data validation solutions

Health Insurance with APCD Submissions

Scaling APCD Data Quality Across States with Automation

Signup for a Demo

See firsthand the difference our solution can make in maintaining compliance and streamlining your APCD payer submissions.

FAQ's about APCD Compliance

What common data validation challenges do medical insurance companies face with APCD submissions?

Many companies struggle with ensuring data accuracy and compliance with state-specific requirements, often leading to rejected submissions and potential fines.

How does Datagaps address the issue of state-specific data submission requirements?

Datagaps offers pre-built rulesets tailored for each state, ensuring that all APCD submissions meet local guidelines and standards effectively and efficiently.

How can insurance companies handle the high volume of rules per file required by APCDs?

Datagaps automates the application of over 150 rules per file, significantly reducing manual effort and increasing the accuracy of submissions across multiple states.

What solutions do Datagaps provide for managing real-time data validation?

Our platform includes real-time alerts and automated reporting features that help identify and resolve issues immediately, ensuring data integrity before submission.

How do Datagaps help reduce the risk of financial penalties for non-compliance?

By automating and rigorously testing each data element against state-specific thresholds and rules, Datagaps minimizes the risk of non-compliance and the associated financial penalties.

Can Datagaps integrate with existing data management systems used by healthcare payers?

Yes, Datagapsโ€™ solution is designed to plug and play with existing data pipelines, offering easy integration with minimal disruption to current systems. 

What measures does Datagaps take to ensure data security during the APCD submission process?

Datagaps ensures end-to-end encryption and sensitive data handling, complying with the highest data security standards to protect data throughout the validation and submission process.

How do Datagaps handle changes in APCD reporting requirements?

Our scalable and flexible solution allows quick updates to rulesets and validation processes whenever states modify their APCD reporting requirements.

What support does Datagaps offer for error investigation and resolution in APCD submissions?

Datagaps automatically segregate records, causing threshold drops or test case failures for detailed investigation, facilitating swift corrective actions without manual sorting.

How does using Datagaps impact the overall efficiency of APCD submissions?

With automated validations and pre-defined templates, Datagaps significantly reduces the time and labor typically required for data checks, enabling quicker and more reliable submissions.

Blogs/Videos

Data Reconciliation for SOX Compliance
Leveraging the Datagaps DataOps Suite for APCD Submissions - Glimpse and Challenges - (Part 1/4)
Challenges with APCD Submissions and Data Validation for APCD Payers Submissions - (Part 2/4)
Benefits of Using Datagaps DataOps Suite for APCD Compliance and Submissions - Part 3
Datagaps DataOps Suite Demo for APCD Submissions - (Part 4/4)
Mastering APCD Compliance: Leveraging DataOps Suite Pre-built Rules for Streamlined Reporting

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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 โ€“ Accelerated by AI Agents.

Data Quality Monitor software

DQ Monitor

Proactive Data Quality with Agentic AI โ€“ 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.

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