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DataOps Suite
The complete platform
Platform Overview
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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
ROI calculator
Estimate the time and cost you’ll save.
Financial services
SOX, BCBS 239 and NAIC MAR

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
Technology Partners
Cloud, data and BI platforms

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Technology Partners

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

Our technology partners

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SI Partners

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

Our SI partners

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CitiusTech logo
Mindtree logo
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Bounteous x Accolite logo
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+6 more partners
Explore Our SI Partners
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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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AnalyticsOps: The Future of Data Management

Is your organization struggling with data quality and workflow inefficiencies? Discover how AnalyticsOps can help you stay competitive.

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What is AnalyticsOps?

AnalyticsOps merges the disciplines of analytics and operations to create a streamlined, efficient, and high-quality data pipeline. It ensures that data is collected, stored, analyzed, and utilized effectively, driving better business outcomes.

what is analyticsops?
Why AnalyticsOps Matters with Gen AI Today?

Enhanced Data Quality

Ensure your data is accurate and reliable, eliminating the risks associated with poor data quality.

Streamlined Workflows

Automate and optimize data processes, reducing manual effort and increasing efficiency.

Scalable Solutions

Adapt to growing data needs with scalable tools and technologies.

DataOps Suite for AnalyticsOps in Gen AI

DataOps Suite for AnalyticsOps

Datagaps DataOps Suite is designed to support and enhance your AnalyticsOps implementation, providing a comprehensive solution that covers the entire data lifecycle.

KEY FEATURES

  • Automated Data Validation and Cleansing: Ensure data accuracy and consistency with minimal manual intervention.
  • Workflow Automation: Streamline complex data workflows, reducing time and effort.
  • Real-Time Monitoring and Alerts: Continuously monitor data processes and quickly identify and resolve issues.
  • Comprehensive Data Integration: Seamlessly integrate data from multiple sources for unified analysis.
  • Advanced BI Analytics Tools: Utilize sophisticated analytical tools and dashboards for better decision-making.

AnalyticsOps Industry Use Cases

Healthcare

Enhancing Patient Care and Operational Efficiency A healthcare provider uses Datagaps DataOps Suite to integrate patient data from various sources, ensuring high-quality data for analysis and better treatment decisions.

Finance

Strengthening Compliance and Risk Management A bank leverages the suite to automate the validation
and monitoring of transactional data, ensuring regulatory compliance and reducing the risk of fraud.

Retail

Optimizing Inventory and Sales Performance A retail chain uses the suite to automate sales data integration
and analysis, optimize stock replenishment, and enhance customer satisfaction.

Manufacturing

Improving Supply Chain Efficiency A manufacturing company implements the suite to streamline
supply chain data operations, reduce bottlenecks, and improve production scheduling.

Why Choose Datagaps DataOps Suite for AnalyticsOps?

Datagaps DataOps Suite is the top choice for implementing AnalyticsOps due to its comprehensive features and exceptional support. The suite covers the entire data lifecycle, offers scalability, and provides a user-friendly interface for easy data interaction and analysis. Additionally, it delivers cost-effective solutions that save time and resources, ultimately leading to a better return on investment.

Expertise and
Support

Extensive expertise in data operations and continuous
support to ensure smooth implementation

Comprehensive
Solutions

All-in-one solution covering the entire data lifecycle, ensuring consistency and reliability.

Scalability and
Flexibility

Scalable tools are designed to fit the specific needs of any organization, from small businesses to large enterprises.

User-Friendly
Interface

Intuitive dashboards and tools that make it easy for users to interact with and analyze data.

Cost-Effective

Efficient solutions that save time and resources, leading to a better return on investment

Ready to transform your
data operations with AnalyticsOps?

Request a demo of Datagaps DataOps Suite today and see how
we can help you achieve unparalleled data excellence.

Request A Demo

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

Our Top Customers Speak

❝ ETL validator is a powerful, user-friendly tool with extensive features, excellent data veracity, and responsive support. Highly recommended for ETL testing. ❞

— Ajit Oak

Director, Head of Business Intelligence Broadcom
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

Latest Blogs

FAQ's about DataOps Suite for AnalyticsOps

How does AnalyticsOps simplify the data analysis process for Data Analysts?

AnalyticsOps automates data preparation tasks such as cleansing and integration, allowing Data Analysts to focus more on extracting insights and less on data wrangling.

How does AnalyticsOps benefit ETL Developers?

AnalyticsOps automates the extraction, transformation, and loading processes, ensuring data is always ready for
analysis without manual intervention. Thus, it increases efficiency and reduces errors.

How does AnalyticsOps help QA testers maintain data quality?

AnalyticsOps provides automated validation checks and real-time monitoring tools, allowing QA Testers
to ensure data quality throughout the entire pipeline.

What specific features does Datagaps DataOps Suite offer for data validation?

The suite offers Gen AI-powered automated data validation rules, anomaly detection, and
comprehensive data quality reports, helping QA Testers maintain high data standards.

How does AnalyticsOps support strategic data initiatives for Chief Data Officers?

AnalyticsOps ensures data governance, enhances data quality, and provides real-time insights, aligning data management practices with strategic business goals.

How does AnalyticsOps facilitate advanced analytics for Data Scientists?

AnalyticsOps ensures that Data Scientists have access to clean, high-quality data and advanced analytical tools, enabling them to perform complex analyses and build accurate models.

Can Datagaps DataOps Suite support machine learning and AI initiatives?

DataOps Suite integrates with machine learning platforms and provides the necessary data preparation and management tools to support AI and ML projects.

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