What this book covers
Chapter 1, Getting Up to Speed – A Review of the Basics, takes you through the basic and essential Tableau concepts needed to get you started.
Chapter 2, All About Data – Getting Your Data Ready, introduces the Tableau data-handling engine, after which we will dive into knowledge-discovery process models, as well as data mining. Last but not least, we will talk about data cleaning.
Chapter 3, Tableau Prep Builder, discusses Tableau Prep Builder, a new member of the Tableau family, and how it can benefit your workflows.
Chapter 4, All About Data – Joins, Blends, and Data Structures, considers the big question that Tableau users face on a daily basis: should I blend, join, or union my data? We will also discuss relationships, join calculations, and spatial joins, which are fairly new features in Tableau.
Chapter 5, Table Calculations, covers functions and table calculations in the process flow and explains why table calculations are still relevant now that LOD calculations are available.
Chapter 6, All About Data – Data Densification, Cubes, and Big Data, discusses data densification and how we can display more granular data than the given granularity of the dataset. We will then move on to cubes and big data, and how to deal with it in Tableau.
Chapter 7, Level of Detail Calculations, helps you understand how to use LODs in such a way that you won't want to live without them any longer, by building a variety of playgrounds to experiment with. We will then combine LOD calculations with table calculations, sets, and parameters to maximize their potential.
Chapter 8, Beyond the Basic Chart Types, introduces some widely used chart types, demonstrating how to extend their usefulness, along with some more unique chart types, all beyond the "Show Me" section. Tableau extensions, a new feature, are explained too, with a couple of examples.
Chapter 9, Mapping, covers Tableau's mapping capabilities using custom polygons, heatmaps, and layered maps, and looks at extending Tableau mapping with other technologies, such as Web Map Services and Mapbox.
Chapter 10, Tableau for Presentations, shows how the user can make use of Tableau for presentation purposes. Tableau is typically thought of as a BI and analytics platform; however, it can be, and often is, used as a presentation tool. In this chapter, you will get some insight into tips and tricks to make the most of this element of Tableau.
Chapter 11, Visualization Best Practices and Dashboard Design, takes you through different formatting techniques and design rules to maximize the aesthetics and utility of your Tableau visualizations.
Chapter 12, Advanced Analytics, will help you test your knowledge using three use cases, which incorporate elements of self-service analytics, time series analytics, and geo-spatial analytics.
Chapter 13, Improving Performance, addresses various aspects of performance on Tableau with the intent of empowering you with techniques to create workbooks that load quickly and respond snappily to end user interaction.
Chapter 14, Interacting with Tableau Server/Online, covers the Tableau Server architecture and its different offerings and functionalities. We will go through the process of publishing, editing, and maintaining your visualizations on Tableau Server.
Chapter 15, Programming Tool Integration, shows how to integrate Tableau with R and Python, in order to implement advanced models such as regression analysis, sentiment analysis, and more in your Tableau projects.
