This is a sequel to Lossless Data Blending via Scaffolding. The blending here is also lossless.

Date dimension is one of the most important dimensions in data structure. Most data are transactional ones with a timestamp attached to each transaction record. Needless to say, time series analysis is one of the most important analysis methods.

Let's get into the problem statement based on a simple example: two stores have their sales tallied in two tables (two data sources). The headquarter wants to view the overall sales along time.

Here are the very simplistic reports from the two stores:
The dates in the two stores are non-inclusive sets. Let's see how to use scaffold to blend the two tables together and create a single chart to view the overall sales.

Scaffolding
As we mentioned in Lossless Data Blending via Scaffolding, we need to build a superset of the dates in both tables. For date dimension it is much easier. It is a two-row table with the min date and the max date of combined set of dates in the two tables:
Note that the Scaffold Primary vs Secondary

1.Show Missing Values
Drag the Date to Columns shelf and turn on "Show Missing Values" in Scaffold's date pill, we will get all the dates in between. This is the KEY in blending date dimension!!

2.Blend Dates
Make sure all date dimensions from the secondary sources are linked with the primary.

3.Use ZN() to aggregate 
We then create a measure Total Sales as
  • ZN(SUM([Store A].[Sales]))+ZN( SUM([Store B].[Sales]))
The ZN() function will fill zero at data marks where it is null. And this allows the two sales values to add. Otherwise, Null + values = Null. Without ZN(), the Total Sales would have been Null as well. So it is a must to use ZN().
Scaffolding with Parametric Dates
Data is dynamic. Especially the end date may not be fixed. We need to change the end date from time to time. It would be hard to change the static scaffold above.

We can use parameters for dates. Thus a parameter's default value and maximum value can be modified easily.

Here is the scaffold:
The we create a calculated field to set up Date dimension:
  • Case [Record]
  • WHEN 1 then [Start Date]
  • WHEN 2 then [End Date]
  • END
Here is the view of the resulting dashboard. Click it to go the interactive version.
This technique has been applied in this calculation:
Taking Stock with Start and End Dates
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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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