Big data is of no use unless you can turn it into information and insight. For that you need big analytics. Every piece of the analytics cycle has been impacted by big data, from reporting, with the need to quickly render reports from billions of rows of data, through advanced analytics like forecasting and optimization, which require complex math executed by multiple passes through the data set. Without changes to the technology infrastructure, analytic processes on big data sets will take longer and longer to execute. It’s not enough now to push the button and wait hours or days for an answer. Today’s advanced analytics need to be fast and they need to be accessible. This means more changes to the technology infrastructure to support these new processes. Analytics companies like SAS have been developing new methods for executing analytics more quickly. Below is a high level description of some of these new methodologies, including why they provide an advantage. Once again, the intention is to provide enough detail to start conversations with IT counterparts (or understand what they are talking about), certainly not to become an expert. There is a ton of information out there if you want more detail. Get the full story at The Analytic Hospitality Executive