Today’s leading businesses, governments, and other organizations collect large amounts of data about their operations and their customers. Classic examples are Amazon, Twitter, or any company that has a call center or provides customer service. All that information is collected and then analyzed in order to predict customers’ future needs, to make sensible purchase suggestions to them, or to market products and services. Google data is another example that can be used for many purposes such as predicting outbreaks of infectious diseases based on sudden spikes in the frequency of certain words being googled.
Building models is an integral part of Predictive Analytics, which is also associated with large amounts of unstructured data and a very broad range of practical applications. Companies are moving from traditional forms of reporting to Predictive Analytics so that they can better react to rapid changes in their business environments. Companies much prefer to be proactive rather than reactive.
In this 2-day workshop you will learn basic skills associated with Predictive Analytics. You will harness the hidden power of Excel and then use more sophisticated tools such as MINITAB® and R.