Text analytics involves applying natural language processing techniques like named entity recognition, sentiment analysis, and topic modeling to extract insights from text data sources. It is used for applications like customer experience, market research, and competitive intelligence. The presentation provided an overview of text analytics approaches and tools, highlighting how it is part of business intelligence and data science solutions. Examples of early natural language processing work from the 1950s were also discussed.