If a model is to yield a result, it needs data. Data are described by a data model, sometimes very simple (‘year’); sometimes more complex (energy consumption by type of energy, …
Author Posts
Data modeling without tears: perils & pitfalls to avoid
Is risk assessment risky business?
As if risks in general weren’t enough, the question is now about the quality of the risk assessment itself. Even more daunting, lists of ‘mistakes in risk assessment’ have been …
Resource use analysis & modeling of recycling, waste prevention, & eco-design
Do we actively poison our environment? Some would say yes – that the substances we artificially produce are positively noxious, pointing to vehicle emissions and sewage as …
Renewable energy analysis: when it’s about the politics, not the grid
How much will renewable energy replace conventional energy this year? Next year? In ten, twenty or more years? Which countries will switch to renewable energy when? To understand …
Do decision support systems impact healthcare?
Nobody is likely to disagree with the notion that decision support systems in healthcare are there to help people make better decisions. When things work well, it is capable of …
Operational risk (OR) scenario analysis: if modeling processes & systems are difficult, try people
Operational risk scenario analysis may sound like a mouthful, but here’s what it’s all about. Firstly, operational risk is the risk to a business of loss from processes, systems …
Which data model will work best for big data?
In the old days (say, pre-Apple iPhone), you could be cool about your data model. Relatively speaking, there wasn’t that much variety in the data to be had in legacy databases or …
How Monte Carlo simulation fights the curse of dimensionality
The Curse of the Mummy? Already tackled with Lon Chaney in 1944. The Curse of Monkey Island? Thousands of PC gamers have beaten you to it. The Curse of Fatal Death?