Data platforms

Streaming operational analytics

Real-time ingestion and processing for telecommunications data using Azure, Databricks and governed data-lake services.

Environment: Azure and Databricks · Focus: Streaming data and operational insight · Pattern: Ingest, process and publish

The challenge

Make fast data usable

Operational events arrived continuously from multiple systems, but teams needed consistent processing, history and access rather than another stream of unstructured messages.

The platform separated ingestion, transformation and consumption so each layer could be governed and operated independently.

Delivery approach

Ingest

Durable capture, schema handling and source-level operational visibility.

Process

Streaming transformations, quality checks and scalable compute.

Use

Curated datasets, dashboards and event-driven downstream actions.

What changed

  • A more reliable route from live events to usable data.
  • Shared controls for quality, lineage and platform operation.
  • Faster access to current operational conditions.
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