Designing a Modern Cloud Platform Enabling Analytics and DevOps for the Government Department - Helium

OVERVIEW

A state government education agency needed to modernise its fragmented on-premises data infrastructure. The goal was a new enterprise-wide information strategy built for data-driven decision-making, advanced analytics and agile concurrent delivery. Omnia was engaged to lead the architecture design of the Enterprise Data and Analytics Platform on Microsoft Azure.

Client Story

Strategy and Priorities:

Move from fragmented legacy infrastructure to an enterprise-wide data strategy — democratising access to data, lifting organisational data literacy and enabling advanced analytics at scale.

Modernize the retail banking experience to retain younger demographics and increase daily app engagement.

Digital Priorities:

Design a secure, scalable, Azure-native Enterprise Data and Analytics Platform supporting data warehousing, analytics, business intelligence and data science — with agile concurrent delivery and DevOps-aligned practices.

Shift from a purely transactional utility to a proactive financial advisory tool.

The Challenge:

Legacy data warehouses and data hubs lacked the scalability, flexibility and capability to support advanced analytics, and data science workloads, or to enable agile concurrent delivery across multiple project portfolios.

Our Collaboration:

Omnia led the architecture design across Information Management, Cloud, Integration and Cyber Security teams — defining a secure, scalable, Azure-native platform to support analytics, reporting and data science workloads across multiple concurrent projects.

We partnered with the bank’s digital and data science teams to design and validate an AI-driven homepage that anticipates user needs and provides tailored financial guidance.

CONTEXT

The Challenge

The agency needed to modernise its fragmented on-premises data infrastructure to support a new enterprise-wide information strategy. The goal was to become data-driven, democratise access to data and lift organisational data literacy. Legacy systems data warehouse and data hubs lacked the scalability, flexibility and capability to support advanced analytics, and data science workloads, or to enable agile concurrent delivery across multiple project portfolios.

OUR EXPERTISE

Omnia led the architecture design for the client's Enterprise Data and Analytics Platform, collaborating with Information Management, Cloud, Integration and Cyber Security teams. The aim was to define a secure, scalable, Azure-native platform supporting analytics, reporting and data science workloads — designed for resilience and agile concurrent delivery across multiple project portfolios.

How we helped

The Solution

Architecture & core technology

Multi-source pipeline development

Adopted lakehouse and data mesh principles using Delta Lake for storage and Azure Synapse — compatible with SQL Server — for data warehousing, enabling both enterprise and portfolio-managed data products.

Built robust data ingestion pipelines connecting cloud platforms, CRM databases and legacy batch systems — standardising ETL/ELT processes across the organisation.

Analytics & flexibility

Cloud data warehouse

The platform was designed for resilience, supporting Power BI analytics, a secure Data Lab for data science and workload isolation and environment separation for concurrent delivery.

Designed and deployed a scalable AWS and Snowflake architecture capable of processing billions of annual transactions — with optimised storage and compute separation for cost efficiency.

Data flows

Data model harmonisation

Supported diverse ingestion patterns across APIs, files, databases and real-time streaming via Event Hub and MuleSoft — with multiple egress options including Power BI, Tableau, secure FTP and API delivery.

Developed a high-fidelity mobile prototype featuring predictive ML spending insights, Gen-AI chat support, and dynamic UI modules.

Final output

Secure data sharing

The engagement concluded with a detailed Solution Architecture Design document covering logical, physical, network, deployment and governance principles — providing a clear foundation for build.

Validated the AI-driven features through extensive qualitative user testing, ensuring the algorithms felt helpful rather than intrusive.

TOOL STACK

Data Automation Stack

Delta Lake

Azure Synapse

Power BI

MuleSoft

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