This document discusses text mining and provides guidance on planning and executing a text mining project. It covers: 1) Choosing the right text mining tool based on factors like cost, reliability, ease of use, and performance. SAS, R, and Python are mentioned as options. 2) The various challenges of text mining like dealing with unstructured, high-dimensional data and validating models without typical analytics metrics. 3) The steps of a text mining process including data loading, cleansing, preprocessing, visualization, insights generation, and validation. Visualizing and gaining insights from text is noted to be difficult.