[ Followup guest post by Hans Romeijn: Calculating Period-To-Date/PoP with Indicators for Better Performance ]

Year to Date (YTD) and Year over Year (YoY) calculations are very important in business dashboards. Jim Dehner recently wrote a great post on the topic. It inspired me to present additional approaches for the issues.

Calculating YTD and YoY without LOD

We have been using YTD and YoY long before LOD (level of details) appeared. So we are not dependent on LOD at all. 

Here is how we calculate YTD, YTD Sales, Previous YTD, Previous YTD Sales and YoY Change %. Note that YTD and Previous YTD can be applied to any other measure's YTD calculations.


An example of using the above formula is provided below and here is the workbook.

What is good about LOD?

With LOD, such as below, it provides portability when using the same value in different sheets with different dimensions. (Caveat: make your filters contextual when using LOD). If you use it in a single sheet, LOD is not a concern. In most cases, we don't need LOD.

Formatting YoY

When calculating YoY change % using the native quick table calculation "Percent Difference", we find that the first column is empty. Visually it's not an agreeable thing, although we perfectly understand why. With a little formatting, we can make the viewers feel better like below. 

Double click the green pill of Percent Difference and use ZN() to wrap around the formula. Then format the pill as follows.

This will put a dash "-" in the empty  column. If you wish, we can put a N/A there. 

Calculations for QTD/QoQ, MTD/MoM and WTD/WoW

Note that you can replace the date part 'year' in YTD/YoY calculations by  'quarter', 'month' or 'week' in both DATEDIFF() and DATEADD() for calculating QTD/QoQ, MTD/MoM and WTD/WoW. Here are the calculations for QTD, Previous QTD, QoQ Change % and respective sales. You can apply QTD and Previous QTD to calculating other measures.

Calculations for QoPYQ: QTD over Previous Year QTD

The condition for the previous year QTD is like 
We also provide calculations for PoPYP: PTD over Previous Year PTD. P is a parameterized period which can be quarter, month or week.

The companion workbook can be downloaded here.

Date Grain and Anchor Date as Parameters

PS. Tom T left a comment below saying that we can use a parameter for the date grain like year, quarter, month and week. That's very true. It will allow user to select a date grain. So here is the parameter Date Grain:

And here is the Period to Date calculation, Period being defined by the Date Grain.

Also Tom also suggested we can use a parameter for the anchor date instead of Today() as in Period to Date. So here is the parameter Date Select:
And here is the PTD Select Date calculation.
And Previous PTD, Period over Period Change % etc are included in the companion workbook. Check it out.

Feel free to leave comments below or contact me at twitter @aleksoft .
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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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