Stakeholder skepticism about machine learning often rings true: If the data scientist hasn’t measured the potential value, then how could the project be pursuing value? Executives know the importance ...

When pitching the use of a model, data scientists rarely report on its potential value. They then experience an unnerving lack of confidence – followed by project failure. When Henry Castellanos first ...

Predictive analytics is one of the most powerful tools at your disposal when it comes to decision-making in Six Sigma. Data drives quite a bit of any business’s operations under Six Sigma, so it ...

Most QA tools manage project and bug tracking. They largely manipulate and organize information gathered in the past, and in so doing, tell you where you are on a project. If they step into the future ...