16 July 2026
Bad Data Blocking AI? Use AI to Fix the Data First
Everyone says you can't build AI on bad data. The flip: AI is now the fastest way to fix that data. A practical playbook with real client metrics.
Insights
Technical Insights
Practical perspectives on data engineering, platform modernisation, and building AI-ready data systems.
14 July 2026
Snowflake Cost Optimisation: 7 Fixes That Actually Work
Cut Snowflake compute spend 30–50% without slowing analytics. Warehouse sizing, query pruning and monitoring tactics from real production deployments.
2 June 2026
Databricks vs Snowflake: Which Platform Do You Need?
A senior practitioner comparison of Databricks and Snowflake — when to use each, when to use both, and how to make the right platform decision.
10 June 2026
Why Most AI Projects Fail Before They Start
The majority of enterprise AI initiatives fail not because of model quality, but because the underlying data is ungoverned, inconsistent, and inaccessible.
5 June 2026
Data Governance for AI Readiness
AI tools need trusted, governed data. This article outlines a practical governance framework that prepares enterprise data systems for production AI adoption.
28 May 2026
Snowflake Cost Optimisation Strategies
Snowflake costs can grow quickly without governance. We cover warehouse sizing, query optimisation, resource monitors, and architecture patterns that reduce spend.
20 May 2026
Building Reliable Data Products
Moving from pipelines to data products means treating data as a first-class product with contracts, SLAs, observability, and clear ownership.
15 May 2026
Common Data Platform Mistakes (And How to Avoid Them)
The eight most damaging data platform mistakes across enterprise organisations — from lift-and-shift migrations to ignoring governance.
12 May 2026
AWS Data Platform Modernisation Guide
A practical guide to migrating legacy data systems to AWS — covering architecture patterns, service selection, cost management, and governance.
8 May 2026
A Practical Data Quality Framework for Enterprise
A hands-on framework for implementing data quality at scale — dimensions, automated checks, tooling, SLAs, ownership models, and quality scoring.
1 May 2026
AI Readiness Checklist: Is Your Data Platform Ready for AI?
A structured checklist across 10 categories to assess whether your data platform is genuinely ready to support AI and ML workloads.
24 April 2026
Modern Data Architecture Patterns for Enterprise
A practitioner guide to modern data architecture patterns — data mesh, lakehouse, event-driven, medallion. When to use each, and anti-patterns to avoid.