Typically, to create the data visualization of a world cloud, different kinds of analytics have to be performed – e.g. text parsing or set certain values for engrams to see which words are close to each other or how large a data set is in one screen. All the different steps that need to be done for a word cloud would each require a different tool with separate steps and data preparation in the open source environment. Teradata Vantage allows an end-to-end analytical process and environment: You access the data, you run the analytics functions – regardless of how large the data is in one screen. For example, the sentiment extractor function in Vantage allows you to get the positives and the negatives; and every single word can be evaluated based on whether it's positive, negative or neutral because it's supervised learning and there's a dictionary that runs on it. The word scores get put together in one particular phrase, and then get visualized using a frequency-based approach. All this happens on exactly one platform – Teradata Vantage – without you needing to do any of these things separately, which is a significant advantage, not only in terms of the amount of time that you save but also in terms of how many different people in the organization you can empower, to be able to do all these kinds of analytics right without people having to actually code and gram splitter etc.