We are entering a new era, the digital age is in full throttle and businesses have computers everywhere ticking away recording a stupendous amount of information, so much of this information is going to waste and companies who don't manage this data and turn it into intelligence are falling behind. Even in highly complex industries, the realization that machine learning will one day cause disruption is coming to the forefront. It most cases effective machine learning programs can be achieved with thousands to hundreds of thousands of observations and companies and starting that process now to really understand what data they need to be collecting, how to gather more data through data mining and how to build a plan for a machine learning future.
Breaking Down Predictive, Prescriptive, and Descriptive Analytics In another Forrester report entitled 'Predictive Analytics Can Infuse Your Applications With An 'Unfair Advantage,'" Principal Analyst Mike Gualtieri points out that "the word 'analytics' in 'predictive analytics' is a bit of a misnomer. Predictive analytics is not a branch of traditional analytics such as reporting or statistical analysis. It is about finding predictive models that firms can use to predict future business outcomes and/or customer behavior." In short, Snow explained that the term "predictive" inherently denotes likelihood over certainty, breaking down the analytics tooling landscape and how it factors into prescriptive analytics. "Descriptive analytics, while not particularly 'advanced,' simply capture things that happened," said Snow. "Descriptive or historical analytics is the foundation on which an algorithm might be developed. These are simple metrics but often too voluminous to manage without an analytics tool. "Generally speaking, dashboards and reporting are the most common use for predictive analytics within organizations today. These tools often lack the link to business decisions, process optimization, customer experience, or any other action. In other words, models produce insights but not explicit instructions on what to do with them. Prescriptive analytics is where insight meets action. They answer the question, 'I now know the probability of an outcome [and] what can be done to influence it in the direction that's positive for me,' whether that be preventing customer churn or making a sale more likely."