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Cloud-Based Analytics and Reporting Platform for Swiss Telecom Industry Leader

Project Duration

6 months

Client Industry

Telecommunications


Target Markets

Switzerland

Technology Stack

Client Overview

We Understand Our Clients Best to Provide them the Best Solutions

The client is a leading telecommunications provider in Switzerland offering broadband, mobile, and digital solutions. They have recently adopted Google Cloud for analytics and performance monitoring and sought to build scalable, dynamic pipelines to centralize insights across web and operational platforms.

Solutions Delivered

Automated Lighthouse reports with real-time dashboards

End-to-end GCP pipeline for performance metrics Centralized reporting for all client properties

Reduced manual work via scheduled transformations

Team Composition

Data Engineer

Cloud Architect

BI Developer

Technical Project Manager

Engagement Type

Contractual hiring

Key Challenges

Key Challenges

Eliminating Data Gaps, Inefficient Reporting, and Weak Customer Understanding

Disconnected

Multi-Source Data Aggregation

Needed a seamless way to ingest data from various internal systems and APIs

Inefficient Reporting

Web Performance Visibility

No centralized dashboard to track website performance metrics across regions

Limited Intelligence

Manual Reporting Overhead

Time-intensive workflows and fragmented cost/performance analysis

Strategic Roadmap

To improve visibility and efficiency, we must automate data pipelines across internal services and third-party APIs, reducing manual effort and delays. Integrating Lighthouse data into a real-time analytics workflow will enable continuous monitoring of web performance. Understanding the metrics that matter most to digital and business teams—such as cost, speed, and uptime—allows us to build unified dashboards that support data-driven decisions and scalable, cross-functional performance management.

● How do we automate data pipelines across all services and APIs?

● Can Lighthouse data be embedded into a real-time analytics workflow?

● What visibility do digital teams need to improve cost-efficiency?

●  How do we empower business teams with unified dashboards?

Execution Approach

Scalable, Automated Infrastructure for Web Performance Analytics

We developed robust ingestion pipelines using Compute Engine and Python to gather data from multiple sources efficiently. Automated Lighthouse reporting was integrated via APIs, enabling continuous web audits without manual intervention.

All data was centralized in BigQuery, with Cloud Functions triggering timely updates to ensure fresh analytics.

To provide accessible insights, we created dynamic Looker Studio dashboards tailored to different stakeholder needs, empowering teams with real-time visibility into web performance, operational metrics, and cost efficiency across regions.

Execution Diagram
Business Impact

BUSINESS IMPACT

Real-Time Reporting Efficiency

Improved Data Accuracy

Accelerated Decision-Making

Cross-Functional Visibility

Business Impact Illustration

35%

reduction in manual data processing time through automation.

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20%

improvement in data accuracy, minimizing reporting errors.

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30%

increase in website performance insights using Lighthouse API.

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25%

decrease in operational costs enabling faster decisions.

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