Azure Stream Analytics

Overview

We build Stream Analytics jobs for windowed aggregates, filtering, and routing from Event Hubs, IoT Hub, or Blob. Queries are checked against sample data, and late-arrival and watermark settings match how late your events really are.

Outputs go to a warehouse, a lake, Power BI, or another hub, with a start policy so a job resumes from a known time after a failure. Streaming units are set from the partition count and reviewed after the first busy day.

What we deliver

• Stream Analytics jobs with windowing, filters, and reference data
• Late-arrival settings based on observed event delay
• Outputs to the lake, warehouse, or a downstream hub
• Start policy, streaming-unit size, and failure alerts

Business benefits

• Aggregates are produced continuously instead of in the next morning's batch
• Late events are handled by a stated policy, not dropped in silence
• A failed job restarts from a known time rather than from the beginning of the day