Cognitive search enables knowledge discovery that is highly relevant to users’ intent by deriving contextual insights from conceptual data. It does this by recognizing the patterns and relationships that exist within virtually any type of information – structured or unstructured, written or spoken. Similar to natural language processing (NLP), this ability to understand data makes it possible to automate manual operations by extracting meaning and performing appropriate actions in real time. Unlike NLP, which focuses solely on linguistics, cognitive search follows a language-independent, statistical approach to understanding human information that is fine-tuned by the use of linguistics. In the age of big data, cognitive search must be able to access diverse data across different formats (text, video, image and audio) and sources (outside and inside the firewall). The underlying content analytics technology is based upon machine learning, continuously learning and adapting as more data becomes available, to achieve the best possible accuracy.