Legacy Data: Making Old Data Work for New Objectives
Adam Brookes - 04/03/2025
Legacy data – the information stored in outdated, and often siloed, systems – is frequently seen as a challenge. The challenge is how to make this old data serve new objectives - such as real-time analytics, customer 360 views, AI-driven insights - without a complete overhaul of legacy systems. Here we focus on different approaches that enable organisations to leverage legacy data in modern architectures.
Designing Scalable Data Architectures for AI
Mark Dyer - 29/01/2025
AI systems rely on vast amounts of data, where data quality is the biggest factor when ensuring model performance, however we must also carefully consider how well the data is structured, processed and made accessible. This article outlines the key strategies for designing data architectures that are robust, scalable and capable of supporting AI workloads in large organisations.
Technology Insights: Most Read 2024
Audacia - 16/12/2024
As we come to the end of 2024, we round up the most popular technical articles read by IT directors, CTOs and other tech leaders on our technology insights blog.
Managing Tech Debt within AI and Machine Learning Systems
Adam Brookes - 27/11/2024
For AI and machine learning systems, technical debt extends beyond code to include complex dependencies in data, models, and operational workflows. In this article, we explore how technical debt differs from traditional software engineering, and actionable strategies with MLOps that can help to manage tech debt effectively.