This chapter is excerpted from the Early Release version of Practical Tableau: 100 Tips, Tutorials, and Strategies from a Tableau Zen Master published by O’Reilly Media Inc., 2016, ISBN: 978-1-4919-7724-8. Shop for Practical Tableau.

Despite being one of the least effective means of communicating data, I often see Tableau pie charts in corporate dashboards and Tableau Public visualizations. New users likely see pie charts as an easy way to spruce up their dashboards, but they are doing themselves a disservice because pie charts increase time to insight and reduce accuracy of insights – the opposite of what we are trying to achieve with data visualization. I’ve talked before about the science behind why you shouldn’t use pie charts, so this chapter will be different.

When I share the shortcomings of pie charts, I am usually asked, “…but if I can’t use pie charts, then how do I show a parts of a whole relationship?” Despite the limitations of pie charts – especially the fact that we can process bars more efficiently than the areas of a pie – this is still one of the most common questions I receive during my Tableau trainings. This inspired me to document some better alternatives to using pie charts in Tableau.

When I was a kid, I enjoyed reading through Choose Your Own Adventure books. In the books, after every few pages, the reader is presented with choices on how they want to proceed. Each choice will point you to a different page number where a story unfolds based on your selection. I assume most kids reading the books were like me and would cheat by going back and forth to experience all of the different outcomes.

Data visualization can be similar in that looking at the same data in different ways often leads to new insights (or storylines, if you will). Further, some end users will have their own preferences for how they want to look at data. Has anyone ever had to convert a data visualization to a crosstab view?

I’ve shown before how to let your end users choose the dimensions and measures being displayed on a chart. This post shows you how to allow your end users to choose the entire chart type being displayed. Both of these user experiences improve engagement and retention of insights.

I’ve often discussed how powerful Tableau parameters are because outside of filters and dashboard actions, they’re one of the only methods for putting control into the hands of your end users. In other posts – all using the power of parameters.

This post will walk you through how to leverage this same functionality in Tableau to allow you and your dashboards’ end users to decide which dimensions or measures are displayed on your views. This is a great approach for keeping analyses focused as well as saving real estate on your dashboard by displaying only one dimension and measure at a time.

Problem: Tableau makes selecting and changing the aggregation of a date dimension very easy while you are building a view. However, unless an end user is viewing an individual sheet in Tableau Desktop, they can’t easily pivot the date granularity between day, week, month, quarter, and/or year on their own.

Solution: Create a parameter that includes each date granularity option you want your end users to have access to (i.e. Day, Week, etc.), and create a calculated field that will act as your aggregation-changeable date.

In many cases, it makes sense to change the granularity of a line graph over time. Take the Sample Superstore data that comes packaged with Tableau, for example. The dataset includes four years of daily data. If you are trying to view your sales over time and you set the date aggregation to year, you are provided a 10,000 foot view of your sales trend, but no seasonal insight. On the other hand, set the date granularity to continuous day, and while outliers stand out, it is nearly impossible to differentiate between individual days because you are looking at more than a thousand marks at the same time.

As you can see, viewing your sales over time at different levels of date granularity will tell very different stories. Why permanently choose the date aggregation of your view when you can allow your end users to choose for themselves?

Parameters are one of the most powerful tools available in Tableau for exploring your data and providing interactivity to your end users. As discussed in An Introduction to Parameters in Tableau, the best way to think of parameters is that they act as wildcards. In the simple , the value of X would be the parameter; in this case, equal to 8. The reason parameters are so powerful is that you or your end users can change the value of X from 8 to any number, which will change the results of a view.

In this post, we will use this concept to create a what-if analysis that will show us what would happen if we improved our sales from 0 – 100%. Parameters come in many different forms, but for this post, we will be creating a parameter from integers, or whole numbers. For this exercise, I am using the Superstore dataset that comes with every download of Tableau if you would like to follow along.