I had a great call with the CEO of a possible partner company for Quantellia this week, where I found myself saying that Decision Intelligence is the “bones” to the “meat” of machine learning.

Our community of big data providers consists of people with wide range of professional and academic backgrounds: Data Engineers, Data Scientists, Data Mining Experts, Data Analyst/Modelers, Big Data Solutions Architects, Visualization Designers, Statisticians, Applied Physicists, Mathematicians, Econometricians and Bioinformaticians.

"use cases seemed to have focused on just a few, very lucrative ones, and that many other applications of this great technology had been left by the wayside. In what appeared to be a bit of winner-take-all"

the fact that a search engine could effectively evaluate truth, and that Google is actively contemplating that technology, should boggle the brain. After all, truth is a slippery, malleable thing — and grappling with it has traditionally been an exclusively human domain.

The world is spinning so fast that it can be hard to keep track of everything going on. And most of us aren't doing a good job of it, writes Hans Rosling.

How does the latest research in neuroscience, psychology, and behavioral economics help us model, influence and improve decision making?

"As a software engineer, I realize I’ve seen this situation before.   It’s what code looks like before it’s been refactored. Because our systems must work efficiently for our companies to survive, software engineers have developed a comprehensive architectural best practice, starting with the concept of code smell ..."

“Pricing is one of those things that till you go and make the change you don’t know what will happen. You go in with a lot more confidence if you have data,” says Anil Kaul, the founder and CEO of Absolutdata, a San Francisco-based firm with offices in Singapore, the Middle East, India, and the United Kingdom. Founded in 2001, Absolutdata now has more than 450 employees.
The company, which has a $20 million investment from Fidelity, specializes in what it calls “decision engineering.” This is the discipline of applying data to your decision-making process in a structured fashion. Among other things, the company provides pricing scenarios based on analytics.

It's time to get serious about world modeling.  Here's why: There are two kinds of software in the world. (1) Tools (like Microsoft word) and (2) software that depends on a model of the world as its core capability Examples of the second category are...

Engineers know how to exercise judgment when data is not available. (Early in my engineering career I was told that, “Engineering is the art of approximation.”) Decision engineers know how to help other people assign probabilities to uncertain events and overcome cognitive biases.

Successful games steer players through their complex systems incrementally, in a sort of feedback loop between player and game that’s as fun as it is difficult, encouraging success and growth instead of defeat.

"...with a decision model, we can see how machine learning, AHP, and machine learning fit into an overall picture of how to make decisions more rigorous, transparent, and agile."

Hello and welcome to World Modeler! 
Quick Study 1 includes a step-by-step guide to the basics of model building, including time-based simulation.  You can download the PDF document, then use it t...

Unlike most data conferences solely geared toward technical aspects, Data4Decisions focuses on the needs of executives and decision makers, uniting the best minds in business and technology to uncover common––and powerful––opportunities to effectively deploy data, make smarter decisions and achieve lasting results.

While the conference tracks will present interactive panel discussions and case studies citing specific examples from targeted industries, attendees will be provided executable insights and actionable takeaways, regardless of their current sector.

The cross-cutting themes will assist decision makers in preparing or advancing their organizations to meet the common challenges associated with security, workforce, ownership, monetization and privacy. 

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