Like many successful businesses, this organisation has grown quickly, adopting various technologies to sustain operations and facilitate future growth.
The challenge:
As the business scaled, so did its tech stack, resulting in fragmented systems and siloed data. This made it difficult to get a clear, unified view of operations. Leaders needed better answers to complex, cross-functional questions, but without a solid data strategy, critical insights (and opportunities) were slipping through the cracks.
Our approach:
We started by analysing and documenting data samples from multiple systems to design a unified, scalable data lake. This included creating a master schema, archiving strategy, metadata repositories, and robust data lineage auditing. ETL processes were carefully optimised to handle different source formats and timings, and partitioning strategies were tuned for performance. The client engaged with Microsoft to pilot an Azure Databricks implementation based on our design.
The result:
The organisation now has a future-proof data foundation that provides a consolidated view across systems. It supports faster, more reliable analytics, reduces manual overhead, and gives teams the visibility they need to make smarter decisions, without the burden of heavy custom infrastructure.
