How do you track trends in Tableau when there is a high degree of fluctuation in our data? Try using a moving average!
A moving average is an average of a collection of points around a specified point. For each mark in our view, Tableau will calculate the average of the mark's value and the value of several previous marks. This creates an average value that "moves" over time.
If you want to reference data that isn't visible in your Tableau worksheet, you're going to need a trick to 'hide' that data rather than filter it out of the worksheet entirely. For example, if you want to calculate year over year growth but only display the latest year, you can't filter the prior year out of your worksheet or Tableau will not be able to reference the prior year values.
Hiding data with a filter in Tableau is an expert trick you should know about. One of the best ways to 'hide' data with a filter is to use a Table Calculation filter. Table Calculations filters are one of the last steps processed in Tableau's order of operations. They are even processed after your standard table calculations (e.g. Percent of Total, Rank, Percent Difference) are computed.
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Sometimes we want to calculate the percent of total of a variable, but those totals add up to over 100%! What's going on?
In those cases, the dimensions we use in the view likely have overlapping members. For instance, a single customer could have purchased at all our stores, meaning that the percent of total for our number of customers is skewed.
Do you ever find yourself working on a data-related project and wonder "What are we doing here?". While data-related endeavors can drive massive values, many of them are fairly directionless. Maybe there's a top-down mandate to "become more data-driven" without much thought about what that actually means.
We believe that the highest purpose of data analysis is to support informed experimentation. Creating dashboards with facts and figures is helpful, but it's really only the first step in the process.
Ready to learn about those additional steps and how you can drive value in your organization? Check out this video on the purpose of data analysis!
Have you ever seen the error: “Cannot mix aggregate and non-aggregate arguments in this function?” If you’ve worked with Tableau for any period of time, you probably have! You could have seen this in an IF statement, a CASE statement, or just a regular calculation!
The big idea is that we can’t aggregate part of our calculated field while not aggregating another part of the same calculated field.
This is because aggregated functions run at a "summary" level, while a non-aggregated function runs at a “row by row” level. So, when we try to use these in one function, Tableau gets confused at exactly how to execute what we’re asking!
Text tables can be overwhelming because they contain a lot of information without using many pre-attentive attributes to draw the users' attention toward areas of interest. One of the best ways to add value to a text table in Tableau is to add totals!
There are numerous types of totals you can add to a Tableau worksheet. You can add totals for Rows, Columns, and can even choose which dimension-level you want sub-totals to display at. In addition, there are some workarounds you can use to display multiple types of totals at the same time.
A messy Tableau data pane is totally overwhelming. It makes finding a particular field a gargantuan task. In fact, you might not even remember what you called the field in the first place! When you finally find the field you want, you realize that you have three very similar fields and you’re not sure what they’re all doing there and which to use!
We’ve all been there.
In this video, I’ll take you through some ideas that I implement to keep the Data Pane as neat as possible so you never need to wander through the Data Pane jungle again.
One of the most important steps to developing a successful Tableau project is the ideation and whiteboarding phase. In the modern world, we often don't get to do that whiteboarding in person. That poses a real change. Whiteboarding in person is instantaneous. It's easy to erase one idea and sketch another. That becomes a lot more challenging in a remote, online environment.
Even the best online sketching tools are a bit clunky, not to mention it's hard to sketch well on a computer screen with a freehand or stylus.
Have you ever needed to use your own colors in Tableau? Maybe you need to use your company’s colors, or a brand’s colors, but you’re not sure how to save those colors into Tableau for repeated use.
You absolutely can add your own custom color palettes to Tableau. You’ll need to add some crucial code to the preferences file to do it!
Over the years, I've had an up and down relationship with layout containers in Tableau dashboard. I remember they saved me on my first big project when I needed to design a worksheet with a dynamic height.
However, then I eventually soured on them. I found them cumbersome and I didn't like how they would show up automatically and force me to lay items out in a particular order.
Over time, I've come back around and have a healthy respect for containers. In fact, I use them in the majority of dashboards I build now. Here are a few key ways I use containers:
Imagine you are building a line graph and want to visually call out the highest and lowest values for your end user. To do that, we can create a dual axis chart where circles representing the MIN and MAX points is overlaid on the line graph.
How can we calculate the highest and lowest values in a Tableau view? These values need to be dynamic (as we filter out info, the values need to change), and they need to be integrated into what we’ve already built. But how can we do that?
If you want to create the best user experience in Tableau, odds are you want to convert your data connections into extracts. Tableau Data Extracts (.hyper) provide the most efficient way to query data in Tableau. Extracts are local snapshots of your data which have been optimized for usage in Tableau.
Extracts can be customized to filter data, aggregate data, and even hide unused fields. Server and cloud-based data sources can support automated extract refreshes on Tableau Server and Tableau Cloud.
Navigating around the dashboards you’ve built can be difficult. How do you build a good homepage? How can you easily toggle from one dashboard to the next without it feeling clunky? Is it even possible for Tableau dashboards to feel easy to navigate?
In today’s video, we answer all those questions. We’ll build a great homepage that allows you navigate to all your dashboards, using icons and buttons. We’ll create dropdown, hamburger menus and a home button to help your users navigate to other dashboards, or go straight back to the homepage.
These skills can make your dashboards feel slick, professional, and user-friendly!
How do you approach a new data set in Tableau? Do you spend a while studying the fields and data types? Or do you Google what other people have built using similar data? Maybe you like jumping straight into building to see how things shake out?
I lean toward the latter. Building visuals allows you to learn the data quickly, develop insights, and expose data issues (let's be honest, there are almost always wrinkles to work out of the data).
Sets are a powerful Tableau tool that can be used in innumerable ways. One of the most useful (and eye-catching!) ways to use sets, is in combination with Dashboard or Worksheet Actions.
This combination allows us to update the values of our sets simply by interacting with our dashboards and worksheets. We can add values to our sets, assign values, or remove values, just based on our clicks.
