See What's Happening Now — Not What Happened Last Week
We build event-driven analytics pipelines on Azure Event Hubs and Databricks Structured Streaming that surface real-time intelligence across hospital operations, factory floors, and EV fleets — so your teams make decisions on current data, not stale reports.
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Batch reporting solves yesterday's problem. Real-time analytics solves today's.
A hospital's bed management team is working from a census report refreshed every four hours. By the time a capacity alert fires, three patients have already been in the ED holding pattern for two hours. Real-time inpatient flow data changes that — surfacing bed availability, discharge readiness, and unit census the moment the status changes in the EHR.
A heavy equipment fleet manager receives an end-of-day report showing a machine ran at 62% efficiency yesterday. The root cause: a vibration anomaly that began six hours into the shift — detectable in real time, invisible in batch. Real-time telemetry from Nayaati catches it in minutes, not the next morning.
A fleet operator needs to know the battery state of charge and charging status of 200 EVs right now — to allocate overnight charging slots and avoid demand spikes on the grid. A nightly export from each OEM doesn't solve that. A real-time streaming pipeline from Azure Event Hubs does.
From event to insight — in seconds, not hours.
Azure Event Hubs
Azure Event Hubs is the backbone of our real-time data architecture — capable of ingesting millions of events per second from IoT sensors, EHR ADT feeds, EV OEM APIs, ERP change data capture streams, and application event logs. Fully managed, infinitely scalable, and natively integrated with the rest of the Azure and Databricks data stack.
Real-time pipelines we've shipped across three industries.
Real-time bed availability, census monitoring, and clinical operations dashboards for a regional health system
A regional health system was managing inpatient flow using static census reports refreshed every four hours. Charge nurses and bed management coordinators had no live view of bed status, discharge readiness, or unit-level capacity — leading to delayed patient placements, ED bottlenecks, and reactive care coordination decisions.
NCompas built a real-time clinical operations pipeline for St. Elizabeth Healthcare using Azure Event Hubs to ingest ADT (Admit, Discharge, Transfer) events from their EHR the moment they occurred. Databricks Structured Streaming applied patient classification logic, joined with room and unit reference data, and wrote enriched results to Delta Lake in real time. Power BI real-time push dashboards surfaced live bed availability, unit census, and discharge readiness — updating with every ADT event fired.
- Live bed availability visible to clinical teams the moment an ADT event fires
- Care coordination teams able to intervene on discharge readiness in real time
- Clinical and operations leadership working from the same live data
Every layer of our real-time stack — and why we chose it.
Azure Event Hubs
Fully managed, millions of events/second, native Azure + Databricks integration, partition-level parallelism for high-throughput sources
Databricks Structured Streaming
Exactly-once guarantees, unified batch and streaming API, native Delta Lake write path, horizontally scalable on Azure
Databricks Delta Lake
ACID transactions on streaming writes, time travel for replay and audit, unified hot + historical store — no Lambda architecture
Delta Live Tables
Declarative pipeline definitions, automated data quality monitoring and alerting, self-healing on stream failure
Power BI Real-Time Push & Direct Lake
Sub-second dashboard refresh, unified BI layer across historical and real-time data, governed semantic models shared across both report types
Azure Logic Apps + Databricks Workflows
Threshold-based anomaly alerts and downstream workflow triggers — maintenance dispatch, care coordination flags, charging reallocation — without custom orchestration code
Pre-built. Production-tested. Deployed in weeks — not quarters.
Nayaati is our proprietary IoT analytics accelerator — purpose-built to compress the time from raw sensor data to live operational dashboards.
- Pre-built pipelines for industrial sensor protocols — no custom build from scratch
- Gold-layer semantic models for OEE, availability, and anomaly scoring
- Enablement embedded into every delivery — self-sufficient from day one
Pre-validated components — no build-from-scratch
Pre-Built Streaming Pipelines
Event Hubs → Databricks Structured Streaming → Delta Lake pipelines, pre-built and parameterized for common industrial sensor protocols and payload schemas. Configurable threshold rules for vibration, temperature, pressure, utilization, and availability metrics. Deploy in days, not months.
Semantic Models for Equipment Intelligence
Pre-built Gold-layer semantic models covering OEE, equipment availability, performance efficiency, maintenance event history, and anomaly scoring — ready to connect to Power BI without custom model development.
Embedded Enablement
Training, documentation, and hands-on onboarding are embedded into every Nayaati delivery — so your operations and analytics teams are self-sufficient on day one of go-live.
Reviews every AI initiative across six governance pillars before it reaches production.
- Policy ComplianceAI usage policies reviewed against org standards
- Data AccessPermissions scoped before model training begins
- Security & IdentityAuth and access controls validated end-to-end
- Technical FitArchitecture reviewed for production readiness
- Regulatory ExposureHIPAA, ISO 27001, SOC 2 and custom frameworks
- Operational ReadinessMonitoring, alerting and rollback plans confirmed
Real-time data powers AI. Continuum ensures that AI is governed before it ships.
Once your real-time analytics pipeline is live, the next natural step is AI — predictive maintenance models on equipment telemetry, length-of-stay prediction on clinical ADT streams, charging optimization on EV fleet data. These are high-value use cases. They are also consequential ones.
Continuum ensures every AI initiative built on top of your real-time data estate is vetted, cost-estimated, and formally approved before it reaches production — whether you're operating under HIPAA, ISO 27001, SOC 2, or your own internal AI governance policy.
What sets our real-time practice apart.
One unified lakehouse — real-time and historical in the same store
We don't build separate hot and cold storage architectures. Your streaming data and your historical data live in the same Delta Lake — governed together, queried together, and powering both your live operational dashboards and your AI models from a single source of truth. No duplicated storage. No reconciliation between a real-time store and a data warehouse.
Power BI for real-time — without adding another tool
Our real-time streaming pipelines are designed to feed Power BI real-time push dashboards and Direct Lake-mode semantic models — so the same BI platform your teams already use for historical and scheduled reporting also shows them what is happening right now. Clinical charge nurses, plant floor supervisors, and EV fleet operators all work in one interface. No additional visualization layer to procure, license, or train your teams on.
Industry-proven in healthcare, manufacturing, and EV
We have shipped real-time pipelines for clinical operations at St. Elizabeth Healthcare, live equipment telemetry for industrial fleets via Nayaati, and EV battery and charging intelligence for Voltera Power. The architecture is battle-tested. The delivery model is repeatable. You are not our proof of concept.
Microsoft + Databricks dual expertise — on the same engagement
Most implementation partners specialize in one platform. We hold Microsoft partner credentials and Databricks partner expertise and deploy them together on the same engagement — Event Hubs feeding Databricks Structured Streaming, Delta Lake powering Power BI Direct Lake, Unity Catalog governing the full lakehouse. You get the right stack, not the one your SI happens to sell.
Your operations are generating real-time data right now. Are you seeing it in real time?
In a 30-minute discovery call, we will walk through your current event sources, your reporting latency today, and exactly what a real-time pipeline would unlock for your clinical teams, plant floor supervisors, or EV fleet operators.
Book a Discovery CallNo commitment. No pitch deck. Just a clear picture of what real-time looks like for your business.
FAQs
Real-Time Analytics — FAQ
Answers to the questions engineering and operations leaders ask before building a streaming data pipeline.