Notes on data, AI, IT
and security
No marketing fog. The way I think about real problems with founders and managers.
Telemetry architecture: collecting sensor data so it is still useful in three years
Why sensor data needs to be designed as a long-term asset, not launched as a one-off pilot that cannot be reused later.
API-first inside the company: why integrations should not happen by word of mouth
How to agree on system interfaces before integration chaos becomes the norm, and why this matters for a growing company.
Security metrics for executives: why virus counts are a bad KPI
How to talk about information security in terms of risk and resilience, rather than technical counters that tell a manager nothing meaningful.
Personal data: map the flows before adding controls
Why protecting personal data starts not with encryption or policies, but with understanding what data the company actually collects and why.
ETL as a production line: where queues, stoppages, and grey operations appear
Translating data integration into the language of manufacturing - so a manager can see bottlenecks in process logic, not in code.
Machine vision for quality control: where it can work today
Not magic and not the future - specific tasks on a production line with clear defect economics and measurable outcomes.
Patching industrial control systems is hard, but no update regime is worse
How to bring operations engineers and security teams to a shared testing and maintenance scheme - without illusions and without paralysis.
Failure as a management scenario: who decides in the first 30 minutes
On why a technical incident is not only an engineering problem, and how to define roles, escalation paths, and a single source of truth before something breaks.
Public cloud SLA: what it says and what it does not
A breakdown of where the provider's responsibility ends and the customer's begins - and why this matters before an incident, not after.
Warehouse robots: the count should go beyond FTE to flow predictability
The economics of warehouse automation are not just about replacing headcount. The real gain is SLA, traceability, and operational stability.
Logs as a data source, not garbage: what you can see before you have a SIEM
How to treat logs as operational material - for diagnostics, audit, and analytics - even without a specialised platform.
Self-service BI: how not to turn reporting freedom into a contradiction factory
Self-service analytics only works with a shared metrics vocabulary and data trust - otherwise every department arrives at the meeting with its own version of the truth.