It’s more complicated than you think. Let me explain.
In my first sample data set I have just the two columns of data below and 365 rows, one for each day of 2018.
I’ll be honest, when Tableau Dashboard Extensions first released with version 2018.2 earlier in the summer, I took a quick glance and moved on. I didn’t have time to dig into it. I kept hearing they “allow you to do the impossible” with dashboards and didn’t understand what they actually did. Fast-forward and I’ve had some time to dig. Here are a few practical things Tableau Dashboard Extensions can do.
When using Tableau, you might occasionally create a worksheet that uses dimensions only. Imagine you created a worksheet displaying an organizational hierarchy that looks like this:
When embarking on a data communication project, you might not always have all the data you need to create a prototype in a timely manner. I often generate realistic, placeholder data sources so I can design a dashboard and get feedback, even if the actual data isn’t ready for display yet.
Have you ever found that Tableau Desktop took a long time to load a worksheet or apply a filter? You might have found yourself wondering “Is my data source too large for Tableau?” The answer is…“maybe”.
Yes, but it takes some wrangling. Unlike Alteryx, there is no “fuzzy match” tool in Tableau Prep, but there is a method you can employ which will help (though, like all fuzzy matching, it isn’t perfect).
Here's an interesting challenges; how do you compare this year's values to the average of the previous 3 years in Tableau? The complex solution requires the use of the FIXED level of detail function. Watch the above video to follow along and learn how to perform this calculation.
Imagine you have a busy worksheet in Tableau that looks like this:
Each line represents a single facility and displays that facility’s overtime hours. Imagine you want to filter to only keep the trends for the 3 facilities with the highest overtime hours from the most recent date BUT you also want that filter to be dynamic so when you update the data there might be a new top 3.
If you have a data set that updates irregularly, figuring out how to filter to show only the latest data is difficult. Relative Date Filters are great but only work well if you have a set time you are filtering to like “today” or “yesterday”. If your latest data could be today, yesterday, or two days ago depending on the refresh schedule, things get trickier.
If you’ve been using Tableau Desktop for a while you probably know that you can join, union and pivot data in the product. When you hear that Tableau Prep helps you “prepare your data” you might wonder what it can do that Desktop can’t.
Yes, you can! Check out the image below for an example.
You don’t.
Tableau Desktop will allow you to union multiple tables from the same database or even multiple .csv files, but you can’t union a table from SQL Server A with a tableau from SQL Server B.
Complex data questions are hard to answer with simple visuals. When questions have multiple components, a single graph may not be enough. For instance, imagine you have a table of data displaying average daily high temperatures by month that looks like this:
If you've ever tried to compare part of your data to the whole in Tableau (and give your users flexibility to change the view), you might think it's not possible. However, with a combination of parameters and calculations, you can give users the ability to compare a partial selection to the whole, original value.
Let’s say you want to compare a value from today to the same day last year to evaluate performance…