Build a Tableau Parameter Action Dashboard

This video is inspired by Filippos Lymperopoulos who has a great article on parameter action concatenation. Definitely check out his article here. I am a hands on person who learns from building and sharing, therefore I put together this video to explore, tweak and hammer home the concept.

In this video we’ll build a Sales Analysis dashboard in Tableau using Parameter Actions and the Concatenation Aggregation functionality. The great thing about this tip is that you can use it across multiple data sources. This is a must see!

This approach relies upon the use of two different data connections. In this manner our data tables are completely un-joined without an established relationship. We have a data-set comprised of a customer list and one comprised of customer transactions across three years.

The key to linking the data sets together relies upon the following calculated field which creates a de-facto set that we can use to highlight customer purchases:

Tableau Concat Calc Field

When we setup a concatenation parameter action on our dashboard, the very act of selecting a [Customer Name] will add that Customer Name to the parameter named [Selected Customer]. This will cause all selected customers to resolve to TRUE, which allows highlighting of the sales bar charts related to the user selected customers.

Tableau Concat Parameter Action Thumb1

In the screenshot above, notice the selected [Customer Name] values on the left hand side are also concatenated together at the bottom of the dashboard (i.e., Franciso Hernandez, Jose Garcia, and Terrye Marchi). All of their respective purchases are also highlighted in the middle of the dashboard.

Tableau Concat Calc Field Label

The above calculated field is used to only show the [QTY] purchased for the user selected customer and is placed on the bar chart label.

Feel free to interact with the viz and download the workbook on Tableau public:

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All views and opinions are solely my own and do NOT necessarily reflect those my employer.

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How to Highlight the Bottom Bar Chart Values in Tableau

 

I decided to make this video after someone left a comment on another video I made titled “How to Highlight the Top 3 Bar Chart Values in Tableau” asking how to find the last three values.

Youtube Comment Highlight Bottom 3

In this video I will show you how to highlight the bottom three sales values on a bar chart. You’ll also learn how to use a parameter to dynamically change the number of lowest bars highlighted.

Bottom 3 Bar Chart Values Thumbnail

We can accomplish the highlighting of the bottom N bar chart values via two ways. We can either create a set or create a calculated field to accomplish this task. The set method is cleaner but has its limitations when multiple dimensions are used in the visual. Therefore, the calculated field approach serves us well when we add multiple dimensions.

Watch the video to see how it all comes together but the calculation boils down to this:

RANK(SUM(0-[Sales]))<=[Highlight Parameter]

By adjusting the [Highlight Parameter] control, the user can determine how many bottom sales values are highlighted in the visual. This method also maintains its functionality when an additional dimension is added to the visual.

As always, If you find this type of instruction valuable make sure to subscribe to my Youtube channel.

All views and opinions are solely my own and do NOT necessarily reflect those my employer.

Create a Tableau Waffle Chart Fast and Easy

In this Tableau tutorial I am serving up some delectable waffles in the form of a fast and easy waffle chart. Watch the video to learn the easiest and quickest way to create a waffle chart in Tableau.

If you’re familiar with the Southeast United States then you know that we love The Waffle House down here. As an homage, I made a simple dashboard in the iconic Waffle House signage style.

A waffle chart depends upon a data connection to the data you wish to visualize and a data connection to the waffle chart template. Once you have these two items setup, you simply create a calculated field that marks the fill percentage in your waffle.

Help yourself to some waffles below:

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All views and opinions are solely my own and do NOT necessarily reflect those my employer.

Create an Interactive Stacked Bar Chart in Tableau

In this post we’ll use the new parameter action functionality in Tableau to create an interactive stacked bar chart. When we select a dimension from the viz, we can drill down into a sub-dimension. Parameter actions are new to Tableau as of version 2019.2. In the video we use an NBA data set which you can download in a workbook if you visit my Tableau Public viz.

This neat little trick relies upon the creation of a parameter named [Team Name Parameter] and two dimensions.

  • Dimension #1 is the [Team Name]
  • Dimension #2 is the [Player Name]

There is an implied hierarchical relationship between [Team Name] and [Player Name] as teams are naturally comprised of players.

We will also create a calculated field named [Player Drill] that is defined as such:

IF [Team Name Parameter] = [Team Name] THEN [Player Name]
ELSE [Team Name]
END

When we place the [Player Drill] calculated field on color on the marks card and setup our parameter actions (watch the video for instruction), the user selection of a [Team Name] on the bar chart will feed the [Team Name Parameter]. This causes all of the players on the selected team to be displayed with their respective breakdown of points scored.

Bonus: There is a FIXED LOD lesson in this video as well as a Star Wars reference which I’m sure you’ll have no issue finding. Here’s a hint:

It’s really not complicated so don’t let all the words here confuse you. Just watch the video and do some great things with your data! Interact with the viz below:

As always, If you find this type of instruction valuable make sure to subscribe to my Youtube channel.

All views and opinions are solely my own and do NOT necessarily reflect those my employer.

This video was definitely inspired by Kevin Flerlage who has a great blog post on the uses of parameter actions in Tableau. Check it out here.

Tableau Sales Dashboard Tutorial using Table Calculations

In this Tableau data visualization tutorial, we’ll learn to use the LOOKUP table calculation function to return sales revenue for the same day last year. A number of different techniques are used in the creation of this dashboard.

I designed this dashboard solely as a teaching exercise to help you understand the LOOKUP function and how to show the same date last year in a separate column.

  • As we learned in a previous video Tableau Table Calculations Simplified, (make sure to watch this video afterwards for more clarity), we’ll compute using specific dimensions and then use “At the level” to make sure our LOOKUP table calculation is performing correctly.
  • The “Show Missing Values” option is selected to fill in date gaps in the data set that do not exist. Ensuring 365 dates per year are present in the visualization enables the offset (i.e., -1) in the LOOKUP calculation to arrive at correct sales revenue from the same day in the previous year.
  • You’ll learn that we can filter on a table calculation by using another table calculation. Filters based on table calculations do not filter out underlying data. Instead, the data is hidden from the view, allowing dimension members to be hidden from the view without impacting the data in the view.

Tableau Order of Operations

Observe the Tableau filter order of operations above. Applying a dimension filter before the Table Calculation filter removes underlying data which affects the proper functioning of Table calculations. Typically, Table Calculations only work on values that are visible in the view. By applying a table calculation (which is last in the order of operations) you preserve underlying data but filter out data from the view.

Interact with this dashboard via the picture link:

You need to read these posts and watch these videos for additional information:

As always, If you find this type of instruction valuable make sure to subscribe to my Youtube channel.

All views and opinions are solely my own and do NOT necessarily reflect those my employer.

Tableau Sales Dashboard Tutorial: Year Over Year Comparison

In this Tableau data visualization tutorial I used a technique shared by Tableau Zen Master Ryan Sleeper to “equalize” dates across the same axis. This date equalization calculated field enables year over year, quarter over quarter, month over month, week over week and same day last year comparisons.

MAKEDATE(2018,MONTH([Your Date]), DAY([Your Date]))

Equalizer 2

Call in The Equalizer for this Analysis

It’s a pretty clever way of preserving the same month and day of date values across many years and updating their respective years to one common year.

For example, all dates would retain their current month and day but would share the year value of ‘2018’. In this manner, data points from various years can be stacked on top of each other for comparison purposes.


Additionally, by creating a parameter value for a specific date part (i.e., year, month, week, etc.,) the user has control over the level of comparisons in the visualization.

You’ll have to watch the video to see the details. Again, thanks to Ryan Sleeper for sharing this tip with the Tableau community which enabled me to apply it to my dataset and share it with you in video form.

As always, If you find this type of instruction valuable make sure to subscribe to my Youtube channel.

All views and opinions are solely my own and do NOT necessarily reflect those my employer.

Tableau Table Calculations Made Simple

In this Tableau tutorial I will discuss a basic quick table calculation and try to demystify what is happening behind the scenes. All of the following will hopefully be made more clear in the video but I’m sharing the text below for reference after you watch the video.

I can’t take credit for the content in this post as the Tableau online help site has some quality information on table calculations which I will reference below. There are two important concepts in understanding table calculations: partitioning and addressing.

Key Concepts with Table Calculations: Addressing vs. Partitioning

The dimensions that define how to group the calculation (the scope of data it is performed on) are called partitioning fields. The table calculation is performed separately within each partition.

Partitioning fields break the view up into multiple sub-views (or sub-tables), and then the table calculation is applied to the marks within each such partition.

The remaining dimensions, upon which the table calculation is performed, are called addressing fields, and determine the direction of the calculation.

The direction in which the calculation moves (for example, in calculating a running sum, or computing the difference between values) is determined by the addressing fields.

So when you order the fields in the Specific Dimensions section of the Table Calculation dialog box from top to bottom, you are specifying the direction in which the calculation moves through the various marks in the partition.

When you add a table calculation using the Compute Using options, Tableau identifies some dimensions as addressing and others as partitioning automatically, as a result of your selections.

But when you use Specific Dimensions, then it’s up to you to determine which dimensions are for addressing and which for partitioning.

At the level (Partitioning)

The At the level option is only available when you select Specific Dimensions in the Table Calculations dialog box, and when more than one dimension is selected in the field immediately below the Compute Using options —that is, when more than one dimension is defined as an addressing field.

This option is not available when you’re defining a table calculation with Compute Using, because those values establish partitions by position. But with Specific Dimensions, because the visual structure and the table calculation are not necessarily aligned, the At the level option is available to let you fine-tune your calculation.

Use this setting to set a break (that is, restart of the calculation) in the view, based on a particular dimension. How is this different from just using that dimension for partitioning? In fact, it is partitioning, but it’s partitioning by position rather than by value, which is how partitioning is defined with the Compute Using options.

Filtering on Table Calculations in Tableau

Filtering on Table Calculations in Tableau can be a bit hacky. More often than not, table calculations are dependent upon the data in the view. That means in order to filter on a table calculation, we need a way to preserve underlying data and only hide data from the view.

Filters based on table calculations do not filter out underlying data in the data set, because table calculation filters are applied last in the order of operations. Instead, the data is hidden from the view, allowing dimension members to be hidden from the view without impacting the data in the view.

Notice in the order of operations diagram below how Dimension and Measure filters are applied before Table calculation filters. When trying to filter on a table calculation (which is dependent upon the data in the view) the results may be unexpected. If we turn our dimension or measure into a table calculation, we can then filter the Table calculation at the appropriate level, which preserves underlying data and only hides the table calculation values we wish to filter from the view.

Tableau Order of Operations

The content in this post was quoted from the sources below.

As always, If you find this type of instruction valuable make sure to subscribe to my Youtube channel.

References:

All views and opinions are solely my own and do NOT necessarily reflect those my employer.