So far, we have talked about data blending via scaffolding: 1,2,3. Blending involves 2 or more data sources.

Data reshaping is about a single data source. By scaffolding, we can alter or transform the data structure in order to create visualizations that was not straightforward using the original data set.

Again, Zen Master Joe Mako has lectured about scaffolding in an hour long video focusing on data reshaping or dealing with a single data source. He has included 4 examples. Here we are going to include 2 more examples.

Why alter the data structure? Because Tableau requires the data set to be in certain structure to be rendered as charts and tables. In other words, we need the right dimensions which can generate the required number of marks.

Example 1. Data Padding Via Scaffold
In this use case, some manager positions are missing in some regions. The rule is to make the assistant manager to be the acting manager. Let's see how this can be done.

So the original data set is as follows
We can see that some of the manager positions are missing. Not all regions have managers. The desired result is as follows:
Let's create a scaffolding which corresponds to the desired structure:
It has 2 dimensions and no measures. All we need to do is to fill the values in this scaffold.

1.Create the scaffolding table in Excel. (Here we have a small table with only 2 dimensions. If more dimensions, see this article for creating multidimensional scaffolding.)

2.Import this table to Tableau as a data source. It will be used as the primary data source.

3.Blend the data set with this scaffolding table.

4.Create a calc field [Employee] in the scaffold, which is a reference to the secondary data set.

5.Create a calc field [Emp++] in the scaffold:
  • IF ISNULL([Employee]) and ATTR( [Title] )='Manager'
  • THEN WINDOW_MAX( [Employee] )
  • ELSE [Employee]
  • END
6.Drag the [Emp++] to the rows shelf and set the table calculation to advanced mode. Set the partition to be Region and move the rest to addressing.
Thus we get the result as expected. The workbook can be downloaded here.

Example 2. Creating a Dimension for Measure Names
It is often desirable that we can use [Measure Names] as a dimension. But we can't. Then scaffolding comes to the rescue. Here is a real life question that Joe Mako helped in solving the puzzle via scaffolding.

The data set is as follows. It is a survey on 3 questions which respondents will answer with yes or no. There are a number of respondents during 4/1/2015 and 5/23/2015.
The goal is to tally the percentage of yes or no per day per each survey question like this:
In the original data set, each question is a column with attribute. There are 3 questions. What we need is a single [Survey] dimension that contains the 3 questions with [Answer] like yes or no. So we build a scaffolding like:
Then we need to build measures like Count and Count % per question per day.
1.Date is created through [Record] with 2 records, that allow us to create Start Date and End Date via 2 parameters. Through Show Missing Values, we get all the dates between the 2 dates. This will allow us to view data per day, per week, per month etc.

2.Create [Answer (Fill)] and [Survey (Fill)]
These two new fields are going to fill every data marks in the table. Total() function is a way to densify the data to where there were no data marks before.
  • Answer (Fill) = Total(Max(Answer))
  • Survey(Fill) = Total(Max(Survey))
3.Create measures Count and Count %
Set them to compute using Date.
4.Thus we get our chart and table to visualize the survey result per day.

So you see how scaffolding is used to create the table and chart! The workbook can be downloaded from here.
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Jake and I collaborated on a dashboard. He told me that he learnt a way to create an in-place help page in Tableau. He first saw it at a conference somewhere and couldn't recall who the speaker was. So I am blogging here about it but the credit goes to somebody else. If anyone knows who the original creator is, leave a comment below.

The key idea is to float a semi transparent worksheet on top of the dashboard, where a help text box is strategically placed on top of each chart. This way, we can explain how to view each chart and what data points are important, etc. This worksheet is collapsible by a show/hide button.

(Addendum: Jonathan Drummey has a much better Tableau-only solution that I missed from his presentation. I only caught later part of the presentation. You might ask him about it if you know him.)

In a recent presentation, Tableau visionary HOF Jonathan Drummey talked about a solution for a variable row heights in a text table. The question apparently came from a perfectionist tableau designer. Tableau is not really made for text processing.

[Forward: I asked ChatGPT o1-mini who then wrote this. Hope it helps. All the credit and the blame go to ChatGPT.

I went over the plan and it looked decent. Whether it can be done in 30 days or not, it depends on the person and the time he spends on it. By the way, ChatGPT can be a really good study buddy. Ask it questions whenever you have any.]

This comprehensive 30-day plan is designed to take you from a Tableau beginner to an advanced user.

Mundane charts are those basic ones that all data visualization beginners can create, possibly with Show Me in Tableau. They are the boring ones at times because many people tend to create fancier ones just to show off. 

I actually like the mundane ones a lot because they are not only easy to create but also easy to be read by the stakeholders.

Pareto chart is a very powerful tool, providing great insights into the data set and into the business at stake.

A while ago, Sharon came to me asking a question regarding Pareto Chart Multiples. That is, per each category, there is a Pareto chart. And we need to create Pareto charts for all the categories. This chart allows us to quickly view the few most important factors that matter to the majority of output in each category. 

Vilfredo Pareto (1848-1923) is the father of the 80/20 rule: 80% of output are produced by 20% of input. It works magically well through all the years.

[Update: The product manager Wilson Po alerted me that the Viz Extension is still a work in progress. It will not be part of the incoming version 2024.1. Instead, it will be released later in 2024. Just be patient]

Tableau 2024.1 is coming. I got a chance to test drive it. As I wrote a bunch of posts on Sankey chart tutorials in the past, I am most excited by the new Sankey chart type. Here I would like to share what I learnt. This is a quick preview. Your comments are welcome.

Buzzfeed recently asked Midjourney to draw images of people in 50 US states.  So the AI drawing tool created 50 images of couples that represent its perception of the people in each state.

I just put the images into a tiled map in Tableau. Each image is added as a background in each tile.

And also I added Viz-in-tooltips to enlarge an image to look at more details.

Feel free to download the workbook and explore it.
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The folks at Business Expert had a brilliant idea. They asked AI's perception on UK banks as a dog. I am inspired to do the same on US banks.

ChatGPT is asked to confess its perceptions on top US banks as a dog. Then Midjourney is tasked to generate the images. Check out what dog is matched to your favorite bank.

All are put together into a single-sheet Tableau dashboard. Feel free to check it out.

Through my previous post on the new Sankey chart type, I got in touch with Wilson, the product manager leading the development of this new chart type. I made some comments on creating multi-level Sankey via cascading of single Sankey's. He told me it can be done already by dropping more dimensions into the Level card.

As an enthusiastic user of Sankey charts, I am excited to learn that a Sankey chart type is being piloted in Tableau Public (Web Edit only). I wrote about Sankey chart design in multiple posts. Sankey chart may appear in different forms depending on applications. 

I played a little with it just to evaluate it. Here are my initial findings and comments.

1. The basic Sankey

I can quickly create a Sankey with 2 dimensions and 1 measure.
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