Last night I was invited to speak at the Chicago Tableau User Group about visualizing time series data. Other than spatial data, time series data is my favorite to visualize. 

There seem to be endless methods for making time series data useful for analysis. Check out this video for 60ish ways to visualize time.

I had a 20 minute slot to present and, of course, I ran over time. I seem to do this with every session I run lately. Be it training for Next-Level Tableau, presenting at events, or running a livestream, I get into a groove and don't want to stop.

I was able to create 14 vizzes in 20+ minutes. I added an extra in this workbook to make the dashboard format nicely.

Click on the image below to download the workbook and dissect it. Get the data here to follow along. 

Have fun! 

During Makeover Monday week 38, Suraj Shah created what might be one of my favorite Makeover Monday vizzes ever.


With his permission, I wanted to try to remake his viz with a different data set. On the last day for DS6 at The Data School, they had a two hour task of creating a viz with the Chicago Taxi data that we used for MM week 6. I figured this might be a perfect data set to give it a go.

I don't like mine nearly as much as Suraj's. It sure was fun creating it though. It took me about 45 min total. There's nothing very complicated about the viz itself, and it's probably this simplicity that I like the most.

Thanks Suraj for the inspiration!! Click on the image below for the interactive version.

Now THIS was a fun week! Eva and Exasol set us up with 105M records to play with. Often time, this can feel like an incredibly daunting exercise, but I took a very methodical approach. More about that in a minute. First, let's take a look at the viz we want to makeover:



What works well?

• Using a line chart to portray a time series rarely is a bad choice
• Nice simple labeling of the axes
• Title tells me what I'm looking at
• Red line on the grey background works well
• The y-axis is truncated, but the chart maintains a nice 3x2 ratio so that the line trends aren't too distorted.

I started by connecting to all 105M records live because I wasn't sure which dimensions I would end up using. When I finally finished (this took well over an hour), I created an aggregated extract. The trick to this is to hide the dimensions you aren't using before you create the extract and to rollup to the lowest date level in the view (month for my viz). This took the viz from 105M to 299K records. Incredibly, the extract was ready in less than 10 seconds. Exasol is crazy fast!

Overall, another fun week. Tonight I get to introduce this to a bunch of new Tableau users at the #MakeoverMonday Live session at Tableau HQ in London. Can't wait to see what they come up with!