From Legacy to Leading-Edge: Accelerating Telco Innovation on Google Cloud

Our impact

• Reduced the time to migrate to Google Cloud by ~40% using our Pathfinder Approach
• Developed a powerful and flexible data platform on Google Cloud, enabling the team to migrate existing data and AI use cases, while facilitating and accelerating the development and deployment of new use cases
• Reduced costs with faster decommissioning of old tools and platforms by enabling faster deployment of data and AI use cases on Google Cloud

The challenge

The company had previously started to build a data platform on another cloud provider, however:

• It only considered consumer-facing use cases
• The platform lacked a post go-live plan, so would be difficult to scale
• The platform didn’t fully address DataOps, including observability and automation, – a key aspect for delivering high-impact use cases at scale. 

They wanted to migrate this platform to Google Cloud, with the following priorities in mind:

1. Speed + cost of the migration: Minimising dual run costs through migrating quickly and iteratively so previous services can be switched off in increments
2. Retention of existing capabilities + value: All Big Data and ML capabilities that currently exist on Big Data Cloud on AWS needed to be available on Google Cloud.
3. Focused code Improvements: Implementing improvements during the migration without extending timelines of the project. 

Our solution

Datatonic set out to develop powerful integrated squads to tackle the large-scale migration effectively. Datatonic’s Pathfinder Team, an experienced squad that creates coding templates and standards, allowed the migration squads to migrate groups of pipelines, data products and ML models as efficiently as possible. 

To execute this large-scale transformation, Datatonic’s powerful, integrated squads worked to build a future-ready foundation on Google Cloud. 

Leveraging Infrastructure as Code, the team seamlessly designed and implemented new environments, while simultaneously validating data and machine learning patterns to standardize and accelerate every stage of development. 

This collaborative effort integrated complex data sources across cloud and on-premises systems, delivering robust templates that eliminated friction for engineering and AI teams. By automating deployment processes and establishing rigorous monitoring, the squads successfully enabled a high-performance DataOps culture. 

This entire journey was further amplified by the Datatonic Academy, which onboarded and empowered the core migration teams with the expert knowledge needed to master the new framework and drive long-term innovation.

This enabled the company to rapidly migrate existing data and AI use cases, accelerate the development of new ones, and reduce costs through faster decommissioning of old tools and platforms. The team is now set up well to deploy new innovative AI + ML models on Google Cloud.

Learn more about data migration.