From hours to minutes — a 360° data infrastructure transformation.
Discover how StradIT modernised a leading investment bank's data infrastructure end-to-end, delivering real-time analytics, a cloud-native data lake, and self-service reporting that turned data complexity into competitive advantage.
A global investment bank running multi-asset trading operations spanning equities, fixed income, foreign exchange, and derivatives. Despite the scale of their operations, their data infrastructure had not kept pace — patching the old system was not the answer. They needed a complete transformation, and StradIT was their best bet.
See MoreData lived in silos across disconnected systems
Reporting ran on slow, outdated batch processes
Analysts spent countless hours on manual reporting tasks
Complex risk models required for FRTB, Basel III, and MiFID II compliance
StradIT's Data Analytics CoE combines deep technical expertise with a practical understanding of how trading floors, risk functions, and compliance teams actually work.
We partnered with the bank and their system integrator, deploying a focused team of four Data Engineers, one Data Scientist, and one Data Architect. This lean, high-impact squad worked side by side with client teams to design and deliver a platform built for speed, scale, and governance.
Explore Data CoEThe bank needed a platform that could unify scattered data sources, deliver real-time insights, and scale gracefully as trading volumes grow. We planned and delivered 100% customised solutions across every layer of their data estate.
See MoreBuilding a cloud-native enterprise data lake
Enabling real-time data ingestion
Creating a unified data model
Delivering high-performance analytics
Empowering business users with self-service reporting tools
Embedding governance, lineage, and audit controls from day one
StradIT assembled a data squad featuring the best minds in analytics and AI — working through a structured six-step approach to bring order to complexity.
We designed and implemented an Enterprise Data Lake on Microsoft Azure, giving the client a centralised repository with elastic storage and compute — a single source of truth for all trading and risk data.
Batch processing was killing the agility of our client. Our data squad introduced real-time data ingestion using Kafka and Spark Streaming, resulting in low-latency processing of trade executions and market data the moment it moves.
We built a Unified Data Model and implemented Master Data Management to eliminate inconsistent data plaguing the bank. This standardised trade data, counterparty information, and reference data — resulting in confusion-free processing across every team.
We deployed a high-performance analytics layer using Databricks and Snowflake for portfolio risk calculations, scenario modelling, and stress testing at speeds simply not possible before. Complex models no longer required overnight runs.
We rolled out self-service business intelligence through Power BI and Tableau, giving traders, risk analysts, and compliance officers the ability to explore data and generate reports on their own terms — no IT ticket required.
We deployed Apache Atlas and Collibra for automated data lineage, governance controls, and audit trails. The bank now has full visibility into the origin of every data point, its transformations, and its intended use.
We help you build a modern analytics foundation that grows with your ambitions — from data lake to real-time insights, governed and production-ready.