Notes on data, AI, IT
and security
No marketing fog. The way I think about real problems with founders and managers.
Open data: what it is and why business should care
Governments and organisations around the world are opening up data for free use. A look at the practical opportunities this creates.
Heartbleed: when someone else's code becomes your problem
The OpenSSL vulnerability showed how much business depends on invisible components that nobody controls and nobody is accountable for.
Industrial robots are getting cheaper: what it means for manufacturers
The cost of industrial robots has been falling for several years. A look at which manufacturing operations this is now a practical question for.
Technical debt: what it means for non-technical founders
An explanation of technical debt through a management lens - where it comes from, how to measure its business impact, and when to pay it down.
Why BI projects stall halfway
A look at the recurring reasons why business intelligence projects fail to reach a useful result, and what to do about them.
Machine learning for mid-size business: what is real, what is not
An honest look at which problems machine learning actually solves for companies without research labs, and which ones remain academic.
The Target breach and the end of perimeter security
What the largest retail data breach on record says about why protecting the perimeter is no longer a viable security strategy.
A data warehouse without a data team
How a small company can build a manageable data warehouse without hiring a BI department or buying an expensive platform.
What to read and watch in 2014 if you are building a system, not a career in hype
A closing post for the year that gives the reader a map of directions, not just a list of fashionable words.
Postdiction 2014-2016: containers, semantics and cloud will grow together, not separately
The winner will not be a single technology stack, but companies that can combine several waves into one platform.
The year in one frame: cloud trust, semantics, containers and a new maturity of the agenda
2013 is changing not the tools, but the direction of architecture and trust in IT.
ML in fraud detection: where AI saves money and where it only complicates the investigation
A look at the decision loop and the explainability problem in machine-learning-based anti-fraud systems.