Infinigate Group
Transforming Infinigate Group’s Data Estate into a Governed Databricks Lakehouse
Infinigate Group partnered with Nimble Approach to modernise its fragmented data estate following significant growth through mergers and acquisitions. With 11 operating businesses using different systems, reporting processes and data practices, Infinigate needed a scalable approach to create trusted, group-wide insight. We assessed the existing landscape, defined a target-state Azure Databricks lakehouse architecture and delivered a prioritised transformation roadmap.
The result was a governed data platform with automated ingestion, more reliable reporting, and a single source of truth, improving access to trusted data and reducing reliance on external support.
Infinigate Group’s Objective
Creating Trusted Group-Wide Data Insight
Following years of successful acquisition-led growth, Infinigate Group required support to bring together a complex data estate spanning 11 operating businesses across multiple continents. Each business had developed its own systems, reporting processes and data practices, creating an opportunity to establish a more connected, governed and scalable approach.
Infinigate needed a solution that would enable consistent group reporting, improve confidence in business performance insights and create a foundation for future growth. Existing data processes included lengthy ETL workloads, manual deployment practices and varied approaches to data management, limiting the speed at which new capabilities could be delivered.
Infinigate’s ambition was to become a data-led organisation, with a modern platform and operating model that could support confident executive decision-making while enabling teams to work more effectively.
Nimble’s Solution
Building a Governed Databricks Lakehouse
Nimble Approach delivered a comprehensive data maturity assessment and transformation roadmap, combining technical discovery with business-led analysis to define the future state. The assessment reviewed architecture, data quality, reporting capability, engineering practices and governance maturity across the Azure estate.
Azure Databricks formed the foundation of the target architecture, providing a governed lakehouse environment where data from across the group could be ingested, refined, and delivered through certified reporting models. Building on this established platform, we designed a metadata-driven ingestion framework using Azure Data Factory, enabling new data sources to be onboarded through configuration rather than bespoke development.
A data control framework was also introduced to provide continuous reconciliation between group reporting and source financial systems, creating a trusted single version of the truth. The roadmap prioritised stabilisation, standardisation, reporting improvements and knowledge transfer, ensuring Infinigate’s internal team could confidently operate and extend the platform.
Driving Faster, Trusted Data-Led Decisions
The modernised platform enabled Infinigate to move towards confident, group-wide data-led decision-making with improved reliability, speed and governance. Optimised Databricks workloads reduced ETL runtimes by more than 50%, ensuring business-critical reporting was available at the start of the trading day.
Automated deployment pipelines reduced a key release process from two hours to 10 minutes, improving delivery speed while increasing consistency across environments. The new reporting ecosystem achieved strong adoption across executive, management and operational teams, with more than 14,000 report views recorded in a single month.
Through the introduction of governed datasets, automated ingestion patterns and a data control framework, Infinigate established a scalable foundation for continued growth, reduced technical debt and empowered its internal team to manage the platform independently.
ETL runtime reduced by over 50%, bringing workloads from more than 7 hours to well under half the previous runtime
Deployment time reduced from 2 hours to 10 minutes through automated CI/CD pipelines
14,000+ report views achieved in a single month across the new reporting suite
Single version of the truth established through governed Databricks lakehouse architecture and financial reconciliation controls
The Technology Stack
In collaboration with DS&D, Nimble carefully evaluated the available technologies in the current tech stack, architecture, and in-house capabilities to select the best technology for sustainable growth.
- Azure Databricks
- Microsoft Azure
- Azure Data Factory
- Azure SQL Database
- Power BI
- Azure DevOps
- Delta Lake
- Figma
Nimble are also continuing to input into the evolution of the DS&D tech stack, including through their ML Ops Operating Model work.
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