The Challenge
Where things stood before
Store operations depended on a legacy Kafka + custom Python service stack that took engineers days to modify. Alerts arrived minutes late and analytics teams couldn't correlate operational events with sales data without a nightly copy.
Our Approach
How we engineered the outcome
- Migrated event ingestion from Kafka to Fabric Event Streams with CDC connectors.
- Deployed an Eventhouse (KQL DB) tuned for time-series workloads with cache-hit >85%.
- Configured Reflex actions to fire Teams alerts and ADF triggers on materialized conditions.
- Enabled OneLake shortcuts to project KQL data into Delta for BI + ML consumption.
- Layered dbt-fabric analytical models on top for historical trend reporting.
The Outcomes
Measurable business impact
<5s
Event → alert latency
85%+
KQL cache-hit ratio
<60s
OneLake shortcut lag
6→1
Vendors consolidated
