Every data source connects once. Fabric handles the rest — unified storage, automated transformation, a governed semantic model, and role-ready dashboards.
Real-time operations intelligence
Every production line, every shift, every KPI — visible in real time. No more waiting for Monday's report to know what happened Friday afternoon.
- OEE, throughput, and downtime updated on each data refresh cycle
- Drill-through from plant level to individual machine detail
- Shift handover dashboards automatically populated at 6AM, 2PM, 10PM
- Anomaly detection flags issues before they escalate into production losses
50+ pre-built connectors. Custom REST connectors available for any source.
+ Any source via REST API, SFTP, or custom Microsoft Fabric connector — scoped to your tenant.
Microsoft Fabric is the first unified analytics platform that combines data engineering, warehousing, BI, and AI in a single product — with one governance layer and one security model.
No data movement. No copies. No silos. All your data lives in a single, governed lake — with every analytics workload reading from the same truth.
Low-code pipelines move, transform, and refresh data on your schedule. New source systems connect in days, not months. No data engineers required on your side.
Define revenue, margin, OEE, or any KPI once — and every report, dashboard, and Excel query uses the same number. No more conflicting spreadsheets.
Data stays in your Microsoft tenant. Row-level security limits visibility by role. Full audit trail. SOC 2 compliant. Your IT team controls everything.
Dashboards live in Power BI — a tool your people know. No new software to buy or learn. Executive scorecards, operational dashboards, and self-service all in one place.
From 10 users to 10,000. From one system to fifty. Microsoft Fabric scales automatically — no infrastructure decisions, no replatforming when your data doubles.
- Map all source systems
- API credentials provisioned
- Fabric workspace created
- Stakeholder kickoff
- Data pipelines built
- OneLake populated
- Transformations validated
- Refresh schedules set
- Business logic encoded
- KPIs defined and tested
- Relationships validated
- Data quality verified
- Role-based dashboards built
- User acceptance testing
- Team trained
- Production go-live