Text analysis provides forward-thinking organizations with a framework to maximize the value of information within large quantities of text. It also helps automate the process by extracting relevant information, interpreting, mining, and structuring information to improve findability, reveal patterns, sentiments and relationships among documents.

At this point, you've learned about different types of analyzers, tokenizers, token filters and their configuration settings, which helps us convert unstructured data/text into terms in a Lucene Index. You've also learned about the approaches for supporting multilingual search using Solr.

In the next chapter, you'll learn about the various ways to import data into Solr.