Notes on data, AI, IT
and security
No marketing fog. The way I think about real problems with founders and managers.
Data contracts: from principle to working tooling
Data contracts were discussed as a concept for several years. In 2026 they are working tooling with real implementation costs and real results.
What data engineering is, and why business needs it before AI
Why companies have to gather and structure data before talking about models and agents.
Streaming data architecture: when it actually changes an operational decision
Streaming data is a popular topic. But for most business tasks, the more useful question is when it is genuinely needed versus when it is overengineering.
Data contracts: the agreement that comes before the pipeline
When two teams exchange data without a formal agreement, the pipeline works until it does not. Data contracts make expectations explicit and incidents avoidable.
Data observability: catching broken pipelines before your users do
A silent data failure is more dangerous than a crashed service. I explain what data observability is and why operational teams need it, not just engineers.
dbt: why this is a question of team discipline, not tool selection
dbt has become a standard for data transformation. But it only creates value when a team changes how it works with data logic - not just by installing it.
Data freshness and operational decisions
When stale data costs money, and how to understand which data in your company needs to be current and which does not.
A data platform versus a collection of tools: how to tell the difference
Why many companies believe they have a data platform when they actually have a pile of tools - and what to do about it.
Lakehouse: a storage architecture without choosing the lesser evil
What the lakehouse approach is and when it solves the real problem of choosing between a data warehouse and a data lake.
Vector databases: what they actually store and when you need one
A plain explanation of what vector embeddings are, what vector databases do differently from relational or document stores, and when the technology is worth adding to your stack.
Data transformation in SQL: why it belongs in a repository
How moving from scattered scripts to versioned transformations changes the maturity of an analytics team.
Data contracts between teams: a simple tool that prevents a class of breakages
What data contracts are, why they solve a problem that technical tools cannot, and how to start without a large project.