Etikett: data analysis

R Markdown is a formatting syntax that makes it easy to create dynamic reports. It’s based on the popular Markdown lightweight markup language for web writing. Markdown Markdown is a response to the growing importance of writing for on-line publication. Tools based around the concept of a printed page (e.g. Word, Google Docs) make little […]

The current obsession with predictive analytics and big data has many organizations fixated on “bottom-up” analysis. Hype has resulted in business leaders thinking there are huge nuggets to be mined from their data lakes—if only they can find the right tools. Time and time again, I see this mindset result in disappointment and disillusionment with […]

Most problems of interest to organizations are multivariate. They involve multiple issues that must be looked at simultaneously. For example, when evaluating sites for a new store, we need to consider factors like cost of land, proximity to transport and local competition. The more issues (i.e. dimensions) we have to consider, the thorny the problems […]

One of the strengths of R is its vast ecosystem of libraries. This includes numerous sophisticated visualization libraries—some of which, such as the excellent ggplot, are capable of producing publication quality charts. I’m not a huge fan of charts (e.g. scatterplots, barcharts) as communication devices. I believe that conclusions can usually be presented more succinctly. […]