Just came across a new book on text mining: Tapping into Unstructured Data: Integrating Unstructured Data and Textual Analytics into Business Intelligence, by William H. Inmon and Anthony Nesavich. I previewed it on Safari and downloaded a few chapters.
The book is not technical in the sense of showing programmers how to code, but it does focus on database architectures and the like. And when they talk about structured vs unstructured, they are really referring to database structures, not necessarily information architectures.
There is a chapter on visualization, but this is disappointing: it’s more about the process of creating visualizations than about whether the visualizations will be meaning to any human being. In fact, one of the examples used is a bar graph, where the bars themselves are blocks and they are stacked in a three-dimensional arrangement—two no-no’s.
One key point they make—a point I made in my presentation at the Euro IA Summit this year in Barcelona—is that for unstructured data to be useful, it often makes sense to bring it into a structured environment. This makes possible analysis and understanding that would otherwise not be possible.
The penultimate chapter is a brief case study on creating a corporate taxonomy. This company in question created one to help them tie together disparate IT systems and to allow analytics to take place at all. Taxonomies still have a place in the unstructured world.
The writing style is dry and not very engaging. And the summaries for each chapter (which I hoped to give me a better overview of the content) are very thin. So, I’m not sure I’d recommend you run out and buy the book, but since I have a Safari account it was certainly worthwhile to go over the content quickly. I plan to read a few key chapters in full later.