ABSTRACT
A data science project is never complete without data visualization. The insights gained through the analytical part of the project may or may not be understood by the audience in raw form. Data visualization makes it easy to present the data and the calculated results to the audience. Before going to the data visualization in Tableau, it is necessary to understand what exactly data visualization is and what does it take to visualize the data in the right form. Once you get the base for data visualization, you can always move toward Tableau. Tableau is highly used not only by the data science domain but also in many other domains where one needs to visualize data to present it to the audience. As a beginner in Tableau, one should always know the difference between a measure and a dimension and how these two features are used in visualizing the data. When handling numeric data, descriptive statistics plays a very important role, and Tableau is efficient in it. This chapter covers all the statistics functions that can be used in Tableau while creating graphs. One of the many add-on features provided by Tableau is the Summary Card, where you can get the entire descriptive statistics in one frame in just one click. Once you know the dimensions, the measures, and the statistical function, you are all set to know the wide support of graphs by Tableau such as the box-whisker plot, the scatter plot, heat maps, etc. When you have created all the required graphs, it is important to merge them onto a dashboard as per the relevance. There are some design principles that one should always consider while creating a dashboard. This chapter mainly covers the basic Tableau knowledge for a beginner, but Tableau does provide some advanced types of charts that can be used to further enhance some of the basic chart types. Also, at the end of the chapter, you will learn to integrate Tableau with Google Sheets that can ease the process of visualizing data from various platforms.
