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The article focuses on the utilization of text mining software by companies to harness the information in their unstructured data. A new generation of text mining tools allows companies to extract key elements from large unstructured data sets, discover relationships and summarize the information. Many organizations are deploying or considering such software to deal with their mountains of text, despite the need for specialized skills to make implementations work. For example, since 2000 Dow's research staff has been using Clear-Research software from ClearForest Corp. in New York to extract data from a century's worth of chemical patent abstracts, published research papers and the company's own files. The text mining software available now does not yet match the accuracy of data mining tools, but vendors are improving their products' ability to understand context, which is key to making text mining tools effective. While there are software systems that analyze both structured and unstructured data, many companies use traditional business intelligence software on their structured data and then turn to separate tools to analyze text-based data. Installing a text miner is generally a simple process. The hard part is getting meaningful results from a process that depends on the skill and knowledge of the person using the software. It takes a skilled analyst to properly interrogate text repositories.