TelecommunicationsData PlatformCloud Migration

Modernizing a Telecom Data Platform on AWS to Enable Analytics, AI, and Data Monetization

A leading telecommunications provider modernized its legacy data platforms on AWS, achieving USD 14.7M in CAPEX avoidance, 50% performance improvement, and improved platform resiliency.

Built on AWS with Databricks Lakehouse Architecture

$14.7M

CAPEX avoidance by eliminating on-premises refresh cycles

~50%

performance improvement for selected workloads

~12 hrs

recovery time (reduced from ~48 hours)

Overview

About the Customer

A leading telecommunications provider in Southeast Asia delivers wireless, home, and enterprise services to millions of customers. Operating at nationwide scale, the organization depends on high‑quality data to optimize network performance, improve customer experiences, and drive data‑led decision‑making across the business.

The Challenge

Business Challenges

As data volumes and analytical demands increased, the telecom provider's legacy, on premises data platforms became increasingly difficult to scale and operate. Years of organic growth resulted in fragmented systems, rising infrastructure costs, and operational complexity that limited the organization's ability to fully leverage data as a strategic asset.
The environment supported multiple business domains, including wireless, home, and enterprise services, but lacked standardization and agility. Data was spread across several legacy platforms, creating silos, duplicated pipelines, and inconsistent data quality. These challenges slowed analytics, reduced trust in insights, and made it difficult for teams to respond quickly to evolving business needs.
Performance bottlenecks further constrained the platform's ability to support large‑scale analytics, AI, and advanced workloads. Scaling capacity up or down required significant effort, and prolonged recovery times increased operational risk. Without modernization, these limitations would continue to impact operational efficiency, delay decision‑making, and restrict the organization's ability to adopt advanced analytics and AI at telecom scale.

The Solution

Solution Approach

OneByZero (OBZ) led the design and delivery of a cloud‑native modern data platform on Amazon Web Services (AWS), working alongside the customer and AWS Professional Services to modernize a complex, legacy data environment. The goal was to replace fragmented, high‑cost on‑premises systems with a unified platform that could scale analytics, support AI adoption, and improve operational efficiency at telecom scale.

Building a Unified Modern Data Platform on AWS

The solution was implemented as a cloud‑native data platform on AWS, centered on a Databricks Lakehouse architecture. The platform was designed to simplify data ingestion, reduce unnecessary data movement, and establish a single, governed source of truth that could be accessed consistently across business domains.

Key Solution Highlights: • Unified data storage and processing: Using a Bronze–Silver–Gold architecture to manage raw, validated, and enriched datasets • Standardized data ingestion and ETL frameworks: To reduce complexity and improve consistency • Centralised governance, cataloging, and lineage: To support data mesh principles while maintaining enterprise controls • Scalable analytics and reporting capabilities: For business users and data teams • A foundation designed to support AI, machine learning, and GenAI workloads: Enabling the organization to improve data quality, accelerate time‑to‑insight, and create a future‑ready platform for analytics and AI‑driven use cases

AWS Services Used

Built on AWS

Amazon Simple Storage Service (Amazon S3)
AWS AppFlow
AWS Identity and Access Management (IAM)
AWS networking, security, monitoring, and observability services
Databricks on AWS

Outcome

Business Outcomes

USD 14.7 million in CAPEX avoidance by eliminating large on‑premises infrastructure refresh cycles and associated operational overhead
~46% of prioritized workloads migrated in the initial phase through a phased modernization approach, accelerating time‑to‑value while minimizing business risk
Up to ~50% performance improvement for selected workloads, enabling faster data processing, analytics, and reporting
Improved platform resiliency, with recovery time reduced from ~48 hours to ~12 hours, enabling workloads to scale dynamically based on business requirements
Improved data quality through automation, with automated data quality controls implemented across key pipelines to support consistent and governed data quality across the platform
Together, these improvements reduced run‑costs, improved operational efficiency, and enabled teams to access timely, reliable insights to support core business decisions.

About OneByZero

OneByZero is a frontier Systems Integrator specialising in AI Coworker design, build, and deployment for regulated enterprises across financial services, telecommunications, and retail. We operate across ASEAN, India, ANZ, and Japan, with a presence in the United States, combining domain expertise in regulated industries with deep AI engineering capability.