The global text analytics market is growing at a compound annual growth rate of 25%per year and is predicted to reach $6.5 Billion by 2020(Frost & Sullivan).Not surprisingly,the applications fueling this growth are business applications such as consumer analytics,operational analytics and fraud and compliance.Nonetheless,semantic analysis is also taking hold in many areas or learning,education and training,ranging from automated alignment of digital resources with educational standards to improved search algorithms and automated content analysis.This presentation reviews the elements of a standard “semantic analysis toolkit” and discusses how this toolkit is applied to customer use cases in training,staffing,law,finance,and education.These use cases illustrate the breadth of tasks and processes that can be sped up and improved by exploiting the ability of a computer to analyze text.At the same time,it is important to realize that text analytics and semantic analysis is not always the best approach to a problem.The final part of this presentation will present use cases where more traditional approaches are “as good” or “good enough” and discuss how to make practical decisions concerning which methods to apply.