Network-Operations Analytics Platform for a US Telecom Leader
A suite of analytics applications on top of an enterprise data lake — turning raw network data into spare identification, inventory visualisation and a live 360° view of the network.
Problem Statement
A large US telecom's network engineering teams were data-rich but insight-poor. Critical operational signals were scattered across systems, making it slow to identify spare parts, understand inventory or get a consolidated view of network health.
They needed purpose-built applications — sitting on top of a data lake — that turned big data into decisions engineers could act on in the moment.
- Operational data siloed across many source systems.
- Slow, manual spare-part identification and inventory checks.
- No consolidated 360° view of network health.
- Business users depended on engineers to answer routine questions.
Business Goals
The outcomes this engagement was designed to achieve.
Our Offering
The services and capabilities Trusty Bytes brought to this engagement.
Data-Lake Applications
Applications built on top of the enterprise data lake to deliver actionable insights and advanced analytics for business users, leveraging big-data frameworks, ETL pipelines and visualisation tools.
360° Network View
A consolidated operational picture that unifies signals from across the network.
Spare & Inventory Insights
Tools for rapid spare-part identification and inventory visualisation.
Feature Enhancements
Ongoing enhancements to a suite of applications supporting the network engineering team.
Scope of Work
- ETL pipeline development
- Data-lake application layer
- Spare-identification tooling
- Inventory visualisation
- 360° network dashboards
- Ongoing feature enhancements
- Insight applications on the data lake
- ETL/analytics pipelines
- Interactive dashboards
- Spare & inventory tools
- Enhancement backlog and releases
- Physical network hardware
- The underlying data-lake platform build
- Field operations
Solution Overview
Trusty Bytes built a suite of analytics applications directly on the client's data lake. ETL pipelines consolidated fragmented operational data, and a purpose-built application layer turned it into spare-part identification, inventory visualisation and a live 360° view of the network.
The applications were designed for business users — not just data engineers — so network teams could self-serve insight and act faster.
Big-data frameworks process network and inventory feeds through orchestrated ETL into curated datasets on the data lake. A React front end with rich visualisations sits on top, backed by an analytics API.
By enhancing an existing application suite rather than replacing it, we delivered value incrementally while keeping the network teams' familiar workflows intact.
Key Features
The core capabilities we designed and shipped — and the value each unlocks.
360° Network View
A single operational picture unifying data from across the network.
Spare-Part Identification
Rapidly locate and allocate the right spare parts.
Inventory Visualisation
Visual, drill-down views of inventory across sites.
Self-Serve Analytics
Business users answer their own questions without engineering.
Technology Stack
System Architecture
A layered analytics architecture: ingestion and ETL feed curated datasets on the data lake, an analytics API serves them, and visual applications turn them into operational insight.
UI Showcase
A closer look at the delivered product. Select any image to enlarge.
How It Works
Challenges & How We Solved Them
Challenge
Operational data was scattered and slow to use.
Our Solution
ETL pipelines consolidated it into curated, query-ready datasets on the lake.
Challenge
Spare identification was manual and slow.
Our Solution
A dedicated application made spare-part lookup near-instant.
Challenge
Business users leaned on engineers for every query.
Our Solution
Self-serve applications shifted routine answers to the business.
Results & Key Highlights
Client Benefits
Future Enhancements
The roadmap we're partnering on to keep compounding value.
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