DataOps Suite Updates: Release 2025.3.0.0 — Faster Velocity, Stronger Governance, Verifiable Data Integrity
This release has been designed to provide data teams with increased velocity, superior governance, and verifiable data integrity. It is replete with platform-wide advancements focused upon the fortification of connectivity, the streamlining of automation, and the augmentation of operational intelligence across the data ecosystem.
What’s New in DataOps Suite 3.0.0?
“Great data is the foundation of great decisions — and DataOps Suite v3.0.0 builds the bridge to trustworthy, timely, and transparent data delivery." – Datagaps Team
1) Data Sources: broader coverage, simpler promotion
End-to end-testing for SAP ASE, IBM AS/400, and SharePoint files – You can now connect these sources and run the full gamut—data quality checks, Dataflows/DB Flows, and end to end validations—just like with your existing systems. SharePoint file validation is enabled via the file component, allowing consistent source to destination testing.
Sync data sources across containers – Move multiple sources from one container to one or more target containers in a single step to save time, reduce handoffs, minimizing drift across environments and keep Dev/QA consistent. This streamlines promotions without manual export/import gymnastics.
Workflow safe renaming and deletion – Rename a data source without breaking dependent workflows; references are healed automatically. If you delete a source, you can select a compatible replacement so pipelines keep running and UI mappings stay intact.
Why it matters
- Extend validation to legacy and enterprise systems without side projects or bespoke tooling.
- Promote test assets faster and more reliably across environments.
- Reduce fragile edits—rename or retire sources with confidence.
2) CI/CD + Git: resolve with context, compare with confidence
Visual conflict comparison (with JSON diff) – When a Dataflow has merge conflicts, the new view highlights local vs. remote changes side by side, colour coded for clarity, and exposes the exact JSON deltas for precise resolution.
Dataflow comparison utility – Compare any two Dataflows—paste JSON, upload files, or pick versions from a list—and review differences visually or at the code level. Great for peer reviews, audits, and validating hotfixes.
Why it matters
- Fewer “mystery conflicts,” faster, more confident merges.
- Clear traceability of what changed and why—without leaving the Suite.
3) Pipelines: maximum parallelism, minimal orchestration overhead
No Dependency Pipeline – Design pipelines where tasks run independently in parallel, backed by persistent queuing via RabbitMQ for fault tolerant, uninterrupted execution. Creation is straightforward, and the results view consolidates status and component level details so you don’t have to jump into individual runs. Choose No Dependency when you need to run many tasks (even 1,000+) concurrently, don’t have intertask dependencies, and want better throughput and fault tolerance with selective task execution for reruns.
Pipeline webhooks – Trigger actions when a pipeline completes, fails, or stops—for example, call external APIs, kick off CI/CD jobs, or send notifications—without polling. Configure responses per event for realtime automation.
Why it matters
- Scale out test and validation workloads without diagram spaghetti.
- Close the loop with downstream systems automatically.
4) Reports & Monitoring: visibility that drives action
Enhanced App Health & Monitoring – Analyze platform performance, track long running queries, and review table sizes. Monitoring now consolidates visibility across containers, supporting both Dataflow and DB Flow for faster detection and triage. Admins can observe CPU/RAM/disk, kill long running repository queries, and quickly see which repository tables consume the most space—all from a central screen.
Why it matters
- Proactive maintenance and targeted capacity planning.
- Fewer surprises in production and clearer ownership of usage.
Upcoming Platform Features
These are the features that will enhance the core functionality and ecosystem of the DataOps Suite itself.
Pipeline Automation:
Drag and Drop capabilities to build testing pipelines in production to ensure that master from Master Data Management systems flows as expected into further downstream systems.
GIT Conflict Resolution:
This is an enhancement to the core platform's Git integration. It will provide a better way to resolve conflicts and merge changes for seamless collaboration.
Schema Drift Tracking and Test Case Auto Healing:
This planned feature will enable the platform to track schema changes and automatically adjust test cases to prevent them from breaking.
Product Innovation Update – Datagaps DataOps Suite Version 2025.3.0.0
Watch the below latest DataOps Suite 3.0.0 product update to see new features in action:
Experience these capabilities firsthand by trying out our product.
Contact us today or explore the full release notes to see how Datagaps DataOps Suite can transform your data operations.
