Notes on data, AI, IT
and security
No marketing fog. The way I think about real problems with founders and managers.
Real-time analytics: when batch is actually enough
Why most companies overpay for streaming analytics where batch processing would be cheaper and more reliable.
Data mesh or central warehouse: choosing without an ideology fight
A practical framework for choosing between a centralised data warehouse and a decentralised data mesh approach - without evangelism in either direction.
Data contracts: the discipline that separates order from chaos
What data contracts are, why they matter for any team passing data between systems, and how to start without complex infrastructure.
Data mesh is an organisational pattern, not a technology choice
Data mesh gets discussed as if it were a tool to buy or a platform to deploy. It is not. Understanding what it actually is changes how you evaluate whether it is right for your situation.
What to understand about embeddings before launching vector search
Why choosing an embedding model is not a technical detail for later, but an architectural decision with long-term consequences.
Vector databases: what changed and why it matters for business
Why vector databases became a topic alongside the LLM wave, and what this actually means for companies working with internal documents.
Operational data and analytics: why they need to be separated
Many companies try to build analytics on top of operational databases. I explain why this creates problems and how to think about the architectural separation.
Data contracts: how teams agree on quality
When multiple teams share data, conflicts of expectation are inevitable. Data contracts are a practical tool for making those expectations explicit.
ChatGPT in the boardroom: the questions founders now ask
The wave of interest in ChatGPT is bringing specific AI questions into boardrooms. I break down what those questions really mean and where to start.
Analytic database versus operational database: when to separate them
Why one database cannot serve both transactions and analytics well - and how to recognise when the time to separate them has arrived.
Supply chain visibility: why the data layer comes before the dashboard
How IoT sensors and real-time data pipelines are changing what companies can know about their supply chains - and where most projects stall.
Kafka and event streaming: what a manager needs to understand
A plain explanation of why companies are switching to event-driven data flows, what Kafka actually does, and when it is worth the complexity.