In this video, we’re going to tackle an interesting little challenge – adding dynamic totals to stacked area charts in Tableau. While this may not be a technique for production-ready charts, it’s perfect for those one-time presentations or exports to PowerPoint.
Recently, I had a fantastic 90-minute private data tutoring session with someone who contacted me via this website. During this session, we worked together to address three different data issues, one of which was the quest to display totals for stacked area charts. With some creative thinking and a dash of Tableau magic, I found a solution that I’m excited to share with you.
Use the timestamps below to navigate directly to your desired point in the video.
If you’re working with data in Excel and need to connect to a SQL Server database, there are a couple of ways to pass parameter values from Excel to SQL Server. In my first video, “Passing Parameter Values from Excel to SQL Server,” I show you how to connect to SQL Server and read values from a cell and pass those values to a native SQL query without using parameters.
Advantage: The first approach has the advantage of being quick and easy to implement. This is because it does not require any additional setup or configuration, such as creating stored procedures in SQL Server. Instead, the values are passed directly to the query, which can be executed immediately.
However, this approach can also be prone to SQL injection attacks, where a hacker inputs malicious SQL code into an input field in order to gain unauthorized access to the database.
Verdict: Speed over Security. Good for Ad-Hoc personal use.
In my second video, “Call a SQL Server Stored Procedure using Excel Parameters,” I demonstrate how to connect to SQL Server from Excel and pass cell values from Excel to SQL Server using a stored procedure. This approach is more secure because the values are passed to a stored procedure rather than a query. It simply requires the setup of a stored procedure in SQL Server, and I show you two ways to accomplish this feat.
Advantage: Stored procedures provide an added layer of security because they can be set to execute with specific permissions, and can be audited for changes and usage. This makes it harder for an attacker to gain unauthorized access to the database or to execute malicious SQL commands.
However, the potential small disadvantage of this approach is that the stored procedures will need to be updated and managed separately from the Excel file.
If you’re new to working with SQL Server and Excel, I recommend watching both videos. The first video will give you a good overview of the basics, while the second video will show you a more secure way to pass parameter values.
I always have fun creating this type of content and sharing with you, my YouTube channel followers.
You can also follow my dapper data adventures on Instagram.
All views and opinions are solely my own and do not necessarily reflect those of my employer
I took the time to produce a dashboard series that would get a relatively new Tableau user up to speed in very little time. I put together the “Goldilocks” videos I wish I had when I was a novice; not too short but long enough to hammer the concepts home.
In the first video, I dive head first into constructing four basic charts that I believe every data user should know how to put together. You will watch me demonstrate how to put together the following charts:
Line Chart with Forecast
The shaded area is a time series forecast predicting the number of orders for the year 2020.
Map
Heat Map
Bar Chart
In the second video, I’ll cover the layout and formatting of the dashboard, as well as adding a little interactivity. When the user hovers the cursor over the Line Chart, all of the other charts will update to reflect the number of orders represented since the selected month and year.
Full Dashboard
Watch Part 1 to Build the Component Charts
Watch Part 2 for Layout and Interactivity
What You need:
Either Tableau or Tableau Desktop
Data set: Tableau Superstore Data (can be found all over the internet with a simple Google search).
Do some great things with your data!
If you find this type of instruction valuable make sure to subscribe to my Youtube channel. All views and opinions are mine alone, independently researched and do not necessarily represent those of my employer.
In this video we’ll learn how to build a bar chart visualization that combines values below a certain threshold into an “OTHER” bucket. This technique is very useful when limiting the number of bars to show on your visualization while not losing sight of all the smaller values.
Using standard Tableau Superstore data, we’ll calculate the percentage of sales that are generated by each individual state.
We’ll then use a parameter to set a percentage threshold where all states below this percentage will be combined.
This technique also requires the use of sets and Fixed LODs.
This technique allows us to combine all states below a certain threshold (e.g., 2%) into one single bar chart showing a combined 24%.
I have to give credit where credit is due to Ann Jackson for sharing this technique at TC19!
Feel free to interact with the viz and download the workbook on Tableau public:
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 of my employer.
Have you ever wanted to stack 4 pie charts on top of each other to build a visual? Let’s have some fun building out a stacked donut chart or a “TrailBlazer” chart as I call it due to its likeness to a particular NBA team’s logo.
Portland Trailblazers anyone?
In order to build out this chart I used an innovative technique shared by Simon Runc on the Tableau forums. Feel free to check out that post here.
Using Tableau’s Sample Superstore Data, Simon came up with an innovative use of the INDEX() function and the Size functionality to create three different pie charts that each show a respective percentage of a measure (in this case Sales) to the Total amount of the measure.
For example, the chart highlights in red the percentage of Consumer Sales as a percentage of all segment sales (i.e., Consumer + Corporate + Home Office). The grey portions represent all other sales, other than the segment of interest.
The trick to this approach is using the Index function to create a pie chart per segment. For example Consumer is assigned a value of 1, Corporate a value of 2 and Home Office is assigned 3. When the INDEX() value is placed on size, the three different charts are assigned sizes where one is slightly larger than the next.
With a little division and axis customization, the three segments are placed on top of each other to provide a stacked pie chart effect. The hole is courtesy of the standard methodology for creating a donut chart which involves a dual axis.
It makes much more sense when you see it in action so make sure to watch the video!
Here is an example of the raw stacked donut chart before the “TrailBlazer” formatting.
Feel free to interact with the viz and download the workbook on Tableau public:
As always, If you find this type of instruction valuable make sure to subscribe to my Youtube channel.
Definitely check out other posts of interest for building donut charts in Tableau:
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.
If you’re interested in Business Intelligence & Tableau subscribe to my Youtube channel.
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!
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.
If you’re interested in Business Intelligence & Tableau subscribe and check out my videos either here on this site or on my Youtube channel.
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!
If you’re interested in Business Intelligence & Tableau subscribe and check out my videos either here on this site or on my Youtube channel.
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!
If you’re interested in Business Intelligence & Tableau subscribe and check out my videos either here on this site or on my Youtube channel.
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