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DataOps Suite
The complete platform
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
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.

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.

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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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Resell, implement or co-deliver

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

Solutions

Use cases

Cloud platforms

BI and analytics

DataOps Suite Feature Updates – Version 2023.4.0.0

DataOps Suite 4.0.0 centers on GIT Integration, letting teams manage ETL/ELT code, BI reports, and test cases in a single Git repository across providers like Azure Repos and Bitbucket for version control, rollback, and CI/CD-enabled collaboration. The release also expands BI testing with Tableau Upgrade, Power BI Regression, and Power BI Upgrade comparisons, introduces Fixed and Delta deviation techniques for anomaly detection, and adds Microsoft Teams integration for real-time notifications and status updates across the data team.

Key Takeaways

  • GIT Integration enables CI/CD for DataOps testing — teams can now store and version dataflows, ETL/ELT code, BI reports, and test cases in a single Git repository (Azure Repos, Bitbucket), with rollback and multi-user collaboration built in.
  • BI regression and upgrade testing expands beyond Tableau — the suite now supports Tableau Upgrade, Power BI Regression, and Power BI Upgrade, comparing baseline vs. live dashboards for both text changes and pixel-level appearance shifts.
  • Two new anomaly detection techniques improve data quality monitoring — Fixed deviation flags data points that cross a set threshold, while Delta deviation flags data points that shift too much from the prior value.
  • Microsoft Teams integration strengthens collaboration — real-time notifications and status updates now surface directly in Teams, keeping the data team informed without switching tools.

If you are interested in getting a demo of DataOps Suite, you can fill your details here.

DataOps Suite Feature Updates – Version 2023.4.0.0

1. Enable CI/CD for your DataOps testing with GIT integration

DataOps Suite with GIT providers Azure DevOps and Bitbucket

DataOps Suite supports various GIT providers like Azure Repos and Bitbucket to store, organize, manage, and track the dataflows of different versions, making it easier to roll back to previous versions if necessary. They provide a centralized repository to manage the dataflows in one place and make it easy for multiple team members to collaborate on maintaining the dataflows.

GIT Integration empowers the Data team to manage their ETL/ELT code, BI reports/workbooks and test cases in a single GIT repository.

Learn More – GIT Integration

2. Improved Testing Capabilities for Tableau & Power BI Reports

DataOps Suite 4.0.0 elevates BI Analytics with enhanced features, catering to both Tableau and Power BI users.
Improved features of BI Analytics

In addition to Tableau Regression, DataOps Suite now supports Tableau Upgrade, Power BI Regression, and Power BI upgrade.

Tableau Upgrade compares the views and worksheets in the newer version with the same views and the worksheets in the older version in the same or different Tableau environments to ensure that no data or formatting has been lost.

Power BI Regression performs a regression testing of the Power BI dashboards by comparing the baseline version of the dashboard (PDF) with the live version. This comparison can be done for ‘text’ which highlights the changes in text even if the text is shifted by a little and ‘appearance’ which performs the pixel-to-pixel comparison and highlights text, chart, etc.,

Power BI Upgradecompares the PDF report in the newer version with the same PDF report in the older version in the same or different Power BI environments to ensure that no data or formatting has been lost.

By automating the regression and migration testing, these components can save organizations time and effort, and help them to ensure that their dashboards and reports are trustworthy and working as expected.

3. “Data Observability” Enhancements

DataOps Suite introduces two innovative detection techniques—Fixed and Delta deviation—for identifying data anomalies.

Data Anomaly techniques

DataOps Suite has introduced two new detection techniques, Fixed and Delta deviation, for reporting the data anomalies.

Fixed deviation is a simple technique where we can set a fixed threshold, and if any data point deviates from the fixed threshold, it is flagged as an anomaly.

Delta deviation is a sophisticated technique that compares each data point to the previous one. If the change in the value of the data point is more than a certain amount, then it is flagged as an anomaly.

Both fixed and delta deviation are valuable tools that can be used to improve the quality, accuracy, and efficiency of data ingestion projects.

4. Collaboration with Microsoft Teams

DataOps Suite strengthens collaboration by seamlessly integrating with Microsoft Teams, providing real-time notifications and status updates.
Collaboration with Microsoft Teams

DataOps Suite collaborates with Microsoft Teams by sending the status of Pipeline and Data Quality rules of the Data Model execution to the channels through “Webhook URL”.

By integrating DataOps Suite with Microsoft Teams, team members can receive notifications about pipeline or data quality rule execution status, errors, and other important notification events directly in Microsoft Teams based on the configured Teams template. This can help to improve communication and collaboration between team members, and ensure that everyone is on the same page.

For more information on other enhancements of DataOps Suite version 4.0.0, read our Release Notes.

Conclusion

Version 4.0.0’s headline feature — GIT Integration — reflects a broader shift in this release: bringing DataOps testing into the same engineering discipline teams already apply to code. Version control, rollback, and CI/CD-enabled collaboration for ETL/ELT code, BI reports, and test cases mean data validation stops living as a separate, manual process and starts moving in lockstep with development. Paired with expanded BI regression coverage for both Tableau and Power BI, smarter anomaly detection through Fixed and Delta deviation, and real-time visibility via Microsoft Teams, this release is less about adding isolated features and more about making testing itself operate like modern software delivery — versioned, collaborative, and continuously monitored.

DataOps Suite – Free Trial

The Datagaps’ DataOps Suite now comes with new components that add extensibility and connectivity with other applications as well as a focus on ease of creating tests by automatically creating SQL Queries and identifying anomalies based on data profile.

Try DataOps Suite Free for 14 days…

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Frequently Asked Questions: DataOps Suite 4.0.0 Release

1) What is GIT Integration in DataOps Suite 4.0.0?

GIT Integration lets teams store, organize, and version-control their ETL/ELT code, BI reports and workbooks, and test cases in a single Git repository, using providers like Azure Repos and Bitbucket, with easy rollback to previous versions.

2) What new BI testing capabilities did version 4.0.0 add?

The release adds Tableau Upgrade testing, Power BI Regression testing, and Power BI Upgrade testing — comparing baseline and live dashboard versions for both text changes and pixel-level visual differences.

3) How does DataOps Suite detect data anomalies in version 4.0.0?

It introduces two techniques: Fixed deviation, which flags a data point when it crosses a set threshold, and Delta deviation, which flags a data point when it changes too much compared to the previous value.

4) Does DataOps Suite 4.0.0 integrate with collaboration tools?

Yes, it integrates with Microsoft Teams to deliver real-time notifications and status updates, keeping the data team aligned without leaving their existing workflow.

Rajesh Kumar A
Rajesh Kumar A

Digital Marketing Manager, Datagaps

Digital Marketing Manager at Datagaps. Drives data-driven growth through content, performance campaigns, and marketing technology.

SPS Murthy
S P S Murthy Akella

Director, Technology Strategy, Datagaps

Director of Technology Strategy at Datagaps. Business solutions architect and Certified Scrum Master in data engineering, responsible AI, and ML across BFSI, telecom, aviation, and energy.

Established in the year 2010 with the mission of building trust in enterprise data & reports. Datagaps provides software for ETL Data Automation, Data Synchronization, Data Quality, Data Transformation, Test Data Generation, & BI Test Automation. An innovative company focused on providing the highest customer satisfaction. We are passionate about data-driven test automation. Our flagship solutions, ETL Validator, DataFlow, and BI Validator are designed to help customers automate the testing of ETL, BI, Database, Data Lake, Flat File, & XML Data Sources. Our tools support Snowflake, Tableau, Amazon Redshift, Oracle Analytics, Salesforce, Microsoft Power BI, Azure Synapse, SAP BusinessObjects, IBM Cognos, etc., data warehousing projects, and BI platforms.  Datagaps

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