Create a Rich, Real-Time Data Lake in Snowflake from 70+ ALM, DevOps, CRM, and ITSM Tools

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Build an Engineering Data Lake in Snowflake

Most analytics pipelines overlook a critical layer: the structured work data from tools like Jira, ServiceNow, and more. This data holds the full story of how decisions are made, features are delivered, and issues are resolved - but it’s scattered, inconsistent, and difficult to analyze in its raw form.

Teams need a way to continuously extract, organize, and normalize this structured work data without disrupting source systems. It must retain full context including history, transitions, ownership, comments, and effort logs and be modeled in a way that’s immediately usable for analytics, AI copilots, and compliance dashboards.

That’s where OpsHub suite of products can help. It does this by extracting structured records from 70+ enterprise tools, applying normalization and enrichment as data flows in. It maintains lifecycle fidelity-including status changes, sprint transitions, comments, and trace links- so what lands in Snowflake is not just a replica, but a contextual, query-ready foundation that can be used for building reliable AI, reporting, and compliance.

• Turn Work Artifacts into an Insight-Ready Snowflake Data Lake

Custom scripts, point exports, and manual transformations often miss critical lifecycle context and break easily as systems evolve. OpsHub provides a low-code, enterprise-ready platform that prepares structured work data for analytics, compliance, and AI-with reliability and without performance risks or data loss.

• Bring Together Data from 70+ Systems into Snowflake

Automatically extract and normalize structured data from tools like Jira, ServiceNow, Jama, Azure DevOps, GitHub, Bit Bucket, DOORS, and more-building a contextual engineering data lake inside Snowflake.

• Enable End-to-End Traceability Across Your Delivery Pipeline

Correlate work items, incidents, and customer interactions across systems to visualize dependencies, reduce silos, and improve delivery insights- from requirements to release.

• Create a History-Aware Data Foundation

Capture the complete lifecycle of every work item-status changes, ownership shifts, comments, effort evolution, and more. This rich, time-sequenced data in Snowflake enables copilots, dashboards, and root cause analysis grounded in context, not just snapshots.

•  Secure, External Architecture

OpsHub runs completely outside your source systems, but inside your premise or secure cloud - no plugins to install, no risk to performance or system stability. This means your end system’s environment stays untouched during upgrades.

• Incremental Pulls Not Full Scans

Instead of hammering your systems with full data pulls, OpsHub syncs only what’s changed. This reduces load on operational tools, speeds up sync cycles, and preserves SLA performance - even as your volume of tickets, work items, issues or cases grows or scale.

• Real-Time Visibility

Sync critical updates in real time so dashboards, copilots, and reports reflect the latest reality - not outdated snapshots. Ensure teams make accurate, confident decisions during audits, AI training, or operational analysis.

• Adapts to Your Schema Automatically

No more breaking syncs when fields change. OpsHub detects and adapts to new fields, workflows, and custom issue types - so your Snowflake models stay clean and current without requiring manual remapping.

• Deployment Flexibility

Deploy OpsHub your way - in Opshub’s secure cloud, on-premises or your secure cloud Whether your enterprise requires data residency controls, air-gapped environments, or cloud-first scale, it adapts to your architecture without compromising security or performance.

Explore how Jira data can tell a bigger story!