Adding a highlight action can be a really nice way to help your end user recognize relationships between data on separate worksheets. However, sometimes the highlight feature doesn’t appear to work properly. Let’s look at an example.
Take a graph like the following:
Let’s say you want to visually distinguish the 5 days with the lowest profit ratio. I’ll show you how I prefer to approach situations like this.
Designing dashboards in Tableau can be tricky. One problem my students run into is how to space worksheets evenly. It is time consuming to drag the edges of worksheets, making minor tweaks, until they are all the exact same pixel width.
It’s easy to want to cram too much information on a single Tableau dashboard. Whenever I have a scenario where I want to provide additional information to my end user without overcrowding my dashboards, I include an info button.
There will be times when building dashboards when you’ll have multiple worksheets that use the same measure on color. It’s best practice to use color consistently throughout your dashboard, but it can also lead to unforeseen complications. Take the below dashboard as an example.
Every dashboard you create is designed to do more than just communicate numbers. It’s a tool with a purpose. That purpose might be to increase revenue, decrease costs, or add value to your product. When creating dashboards, I like to keep that purpose forefront in my mind.
A powerful addition you can apply to your dashboards right now is to lead with questions. When you change the title of your dashboard into a question, you turn your audience from passive viewers to active viewers. They aren’t just reviewing numbers, they are now trying to answer a question.
It’s easy to be more complex than necessary. It’s hard to be simple and succinct. As Mark Twain said, “I didn’t have time to write a short letter, so I wrote a long one instead.” The same is true in the world of data analysis.
Most people just want to know: “based on what’s happened (data), what should I do next?”
One of the things I found most confusing when I first started using Tableau was trying to figure out what all the different files types do. It’s not exaggerating to say that I lost sleep over it. I want to provide you with a brief overview of the primary file types you’ll encounter and their primary uses.
I shared an example with a class recently about how to use Table Calculations in Tableau and got a request to share this via a write-up. One of the most powerful things about Table Calculations in Tableau is the ability to set a scope and direction.
One of my favorite additions to a dashboard are summary tiles. They’re a great way to quickly communicate a few quick, important data points. In this write-up, I’ll share some of my favorite techniques for building them and making them look crisp. See below for an example of summary tiles I created recently.
If you’re ever refreshed an updated Excel file in Tableau and noticed that your data didn’t change, this write-up is for you. The main issue is that when you save your Tableau Workbook as a .twbx packaged workbook file, it will often package the Excel file in a temporary file structure so that it can be easily shipped along with the workbook when shared.
Not only is Tableau a great data analysis tool, it’s also really useful for data discovery. One of the helpful ways you can use Tableau is to uncover inconsistencies and holes in your data structure. I do this by finding out what data unexpectedly has null values.
I recently got an email from a former student explaining that they were trying to recreate something similar to the image below in Tableau.
The trouble she was running into was recreating the total header called “Planned Cost by Perf”. If you try to use a measure as a discrete header, you end up with the value summed for each partition. Here is an example using Superstore data:
When calculating growth rates from one date period to another, it’s important to compare apples to apples. For instance, when building a graph in Tableau to compare quarterly sunscreen sales in Seattle, I probably wouldn’t want to compare Q3 Sales (July - September) to Q2 Sales (April - June) because there will be more sales in Q3. The product has a cyclical sales cycle. Instead, I would rather compare Q3 Sales of this year to Q3 Sales of last year to more accurately understand growth rates.
Comparing progress against a goal in Tableau is a common use case and I wanted to share a few tips about how I like to do this.
Tableau is usually the last 20% of any data communication effort. What is the first 80%? This document is meant to provide an example of what the finished output of data preparation for Tableau should look like.