Data foundations case studies
At Scott Logic, we advocate for pragmatic data architectures that make your data usable, accessible and secure. Here are a couple of examples from clients we've supported...
Building confidence in compliance data
A global natural resources business needed to improve its trade surveillance capability, but stronger analysis depended on stronger data foundations. By making complex, varied datasets more reliable and easier to work with, the organisation could give compliance teams greater confidence in the insights they used to assess activity.
The challenge
New compliance requirements created an urgent need to evolve the client’s trade surveillance capability. The organisation had already invested in a new data lakehouse, but as data volumes grew and sources became more complex, the existing setup was harder to maintain and less able to support analysis that compliance teams could trust.
The project
The project underlined a simple point: advanced analytics is only useful when the data behind it can be trusted. Without reliable data flows, clear ownership and repeatable processes, teams spend more time questioning outputs than acting on insights.
Scott Logic helped the client turn a complex data environment into a stronger foundation for trade surveillance. By clarifying how data moved through the organisation, improving key processes and helping internal teams retain critical knowledge, we gave compliance teams a firmer basis for analysis and reduced the uncertainty that had slowed their work.
The impact
The project gave the client greater confidence in the data foundations supporting its surveillance activity, making future analysis easier to trust, explain and extend. It also reduced reliance on fragile processes and individual knowledge, leaving the organisation better placed to respond to changing business and compliance requirements.
From legacy data feeds to future-ready insight
A large UK government department wanted to move beyond legacy data feeds and create a reliable foundation for understanding how people interact with its digital services. The aim was to make data more consistent, connected and trustworthy, so future analysis could support better decisions with confidence.
Advanced analytics, AI and automation are only useful when the data behind them is consistent, connected, secure and available at the right level of detail. Without those foundations, analysis risks being slow, partial or misleading.
The challenge
Important data existed across multiple systems, but it was fragmented, inconsistent and not available at the detail or frequency needed for meaningful analysis. That made it difficult to build a dependable view of customer journeys or use more advanced techniques with confidence.
The project
We helped the department design, prototype and evolve an event-based data architecture that allows systems to publish and consume data consistently. Working across infrastructure and data design, we made sure the solution met governance expectations, supported long-term operational use and gave the department a dependable base for analytics.
The architecture brings together contact, business process, support and outcome events to create a longitudinal view of customer journeys. This gives data professionals a clearer picture of how services are used and helps them generate insight from lower-level, more frequent data.
The impact
The department now has a stable, secure and reusable data product at the heart of its analytics capability. By reducing reliance on legacy feeds and establishing new patterns for data access and consumption, the work has strengthened the foundations for future digital services, better decision-making and improved outcomes at lower cost.
It has also created the conditions for richer analysis of customer journeys, including the ability to combine event data with large volumes of free text feedback such as complaints and surveys. This gives the department a more rounded understanding of service performance and user experience, and a scalable foundation for future insight, advanced analytics and AI-enabled service improvement.
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