Make Flashy Maps in Tableau with Mapbox

The default maps in Tableau are just fine but sometimes you need to kick up the flamboyancy factor in your visuals. Integrating maps from Mapbox with Tableau is the perfect way to add some Liberace flash to your development game.

Mapbox is an open source mapping platform for custom designed maps.  By creating an account with Mapbox, you can either design your own maps on the platform or use their preset maps, which are all more impressive than the out of the box option in Tableau.

All you need to do is enter your generated API token (provided by Mapbox) into Tableau’s Map Services interface and you’ll have access to some pretty impressive mapping options.

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How to Drill into Data Using Set Actions in Tableau

Drilling with Set Actions

If you’ve ever tried to use the default drill functionality within Tableau, you know that it could be a more user friendly experience. The default table drill functionality opens all of the options at the next drill level which can force a user to lose sight of the data upon which they’re focusing. A more user-friendly option enables the user to only drill into a specific selected value where focus and attention can be maintained. This is otherwise known as asymmetric drill down.

Fortunately as of version 2018.3, Tableau has added Set Actions as a new functionality. At a high level, developers can take an existing set and update its values based upon a user’s actions in the visualization. The set can be employed via a calculated field within the visualization, via direct placement in the visualization or on the marks card property.

In lay terms this means empowering a user with more interactivity to impact their analyses.

In this first video, I’ll demonstrate a use of set actions on an NBA data set. We’ll drill from Conference to Division to Team to Player. This tip will be easily applicable to your Tableau data. And with the bonus tree-map tip you’ll release your inner Piet Mondrian.

Feel free to interact with the set action example on Tableau Public and then download and dissect the workbook.


Drilling with Level of Detail (LOD) Calculations
If you want to stay with a classic approach, a nice Level of Detail (LOD) workaround can be employed to drill into the next level. Here is a tip that accomplishes a similar outcome where I demonstrate a technique originally presented by Marc Rueter at Tableau Conference 2017.

Now that I’ve equipped you with the knowledge to incorporate customized drilling functionality into your analyses, go forth and do some great things with your data!

References:

https://onlinehelp.tableau.com/current/pro/desktop/en-us/actions_sets.htm
https://www.tableau.com/learn/tutorials/on-demand/set-actions
https://www.basketball-reference.com/leagues/NBA_2018.html
https://www.youtube.com/watch?v=d22A4XVoUEs

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Add a “Filters in Use” Alert to Your Tableau Dashboard

In this video we will learn to add a “Filters in Use Alert” to a Tableau Dashboard. If you have a dashboard with multiple filters, apply this quick and easy tip to inform your users that filters are in play. This tip builds upon the dashboard that I showcased recently in a previous post: Add a Reset All Filters Button to Your Tableau Dashboard.

I learned this current tip from a presentation given by Tableau Zen Master Ryan Sleeper, so I have to give credit where credit is due.

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Add Totals to Stacked Bar Charts in Tableau

 

In this video I demonstrate a couple of methods that will display the total values of your stacked bar charts in Tableau. The first method deals with a dual axis approach while the second method involves individual cell reference lines. Both approaches accomplish the same objective. Hope you enjoy this tip!

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Tableau K-Means Clustering Analysis w/ NBA Data

Interact with this visualization on Tableau Public.

In this video we will explore the Tableau K-Means Clustering algorithm. K-Means Clustering is an effective way to segment your data points into groups when those data points have not explicitly been assigned to groups within your population. Analysts can use clustering to assign customers to different groups for marketing campaigns, or to group transaction items together in order to predict credit card fraud.

In this analysis, we’ll take a look at the NBA point guard and center positions. Our aim is to determine if Tableau’s clustering algorithm is smart enough to categorize these two distinct positions based upon a player’s number of assists and blocks per game.

Nicola Jokic is a Statistical Unicorn

If you also watch the following video you’ll understand why 6 ft. 11 center Nikola Jokic is mistakenly categorized as a point guard by the algorithm. This big man can drop some dimes!

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Create Multiple KPI Donut Charts in Tableau

In honor of National Doughnut Day (June 1st), let’s devour this sweet Tableau tip without worrying about the calories. In this video I we will create a multiple donut chart visualization that will display the sum of profits by a region. Then we’ll use the donuts as a filter for a simple dashboard. Once you finish watching this video you’ll know how to create and use donut charts as a filter to other information on your dashboard.

I know that donuts are not considered best practice, (especially when negative numbers are involved) but they have their uses. Assuming you know that bar charts are a best practice, it never hurts to learn other techniques that add a little “flair” from the boring world of bar charts.

Have you ever looked at a Picasso painting? Obviously Picasso was well versed in painting best practices (understatement) but in some of his art, the people are not rendered in the best practice. Always learn the best practices, but know when to leave them behind and add a little flair! (In no way am I comparing myself to Picasso).

Three-Musicians-By-Pablo-Picasso

Three Musicians – Pablo Picasso

Three Musicians by Picasso is not best practice but it is a work of art!

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How to Use Jittering in Tableau (Scattered Data Points)

 

In this video I will explain the concept of jittering and how to use it to scatter your data points in Tableau. In a normal box plot Tableau data points are stacked on top of each other which makes it more difficult to understand positioning. By using this simple tip combining a calculated field a parameter, you will be on your way to gaining a better understanding of your data points. We’re going to get our “Moneyball” on by analyzing average NBA player points per game in the 2016 season.

If you’re interested in Business Intelligence & Tableau subscribe and check out my videos either here on this site or on my Youtube channel.