One of the beneficiaries of big data hype is text mining or text analytics as textual data, for example blogs, tweets, product reviews, and Facebook, is everywhere and companies are developing tools to mine this data. In a recent report from Gartner, text analytics is seen to be growing rapidly in next few years providing substantial business benefits. To be a successful text miner requires a good knowledge of machine learning, information retrieval, and natural language processing. Often there is a confusion about what exactly are the tasks handled by text mining and how. In this connection, I came across a succinct visual representation, shown below, in a recent article in Analytics that I thought I should share with others who may find it useful.