Using LODs instead of WINDOW

As a consultant, I am asked to find solutions to a variety of issues. Last week, I was working for a client that had created a dashboard to track when values were outside of expected ranges (any monthly value falling outside two standard deviations from their three-year average). The dashboard showed monthly indicators for 37 months (the current month and 36 months prior).

To demonstrate the issue, I have replaced the data source with Superstore. You can download the accompanying workbook from Tableau Public.


This view was ideal for their analysts, in that they could see historical trends of these indicators. However, the supervisor wanted a more summarized view – one that would only show those subcategories outside of the norm for the current (or selected) month.

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#WorkoutWednesday – 2018 Week 2

It’s a new year and with it comes a new team of curators for my favorite weekly activity: WorkoutWednesday. This week, Zen Master Rody Zakovich took over the reigns. Joined by Luke Stanke, the two rolled out a new website for the challenge. I have admired Rody’s work over the years and look forward to what he is has in store for us this year. And it seems as if Luke is definitely ready to come up with his own puzzling exercises.


This week’s challenge:

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Storytelling with Data Challenge – Jan. 2018

One of my personal goals for 2018 is to become a better story teller. As a consultant, I am often restricted to telling the story my clients want to hear. All too often, I find this story to be too all-inclusive and lacking focus. But, hey, that’s what the clients want. But when it comes to projects where I have more say in the matter, it seems all too often that this style that I am so often used to accommodating for takes over. Lately, I have found it more difficult to focus my visualizations into a single powerful arching story.

Towards the end of 2017 I started seeking out resources to help me become a better story teller, or more specifically, return to a time of simply being able to tell even a single story. I had previously read some blog posts by Cole Nussbaumer Knaflic and decided to revisit it once again. To my pleasant surprise Cole had recently started a podcast, and I quickly made time to listen to these while playing in a recent poker tournament. Her first episode resonated strongly with me with how to provide feedback to others on visualizations, and more specifically to consider the constraints at which someone had when creating their visualization. I think we miss this fact way too often.

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Learning Tableau via Reverse Engineering

When I first started to learn Tableau, I first went to the Tableau website and watched every training video. I played around with Superstore and quickly jumped into using my own business data. I began by duplicating existing Excel reports in Tableau, but eventually branched out and started creating my own true dashboards. I was one of the few people in my department actively using Tableau. Because of this, I didn’t really have anyone I could go to for advice or assistance. Thank goodness for the amazing Tableau community! I would search the forums for ideas for different types of dashboards, and more importantly answers to questions on how to get Tableau to do exactly what I wanted it to do.

That was in 2012, and in the years since I have learned more from the Tableau community than I ever could from videos or training classes. I have downloaded countless workbooks from the forums and Tableau Public, pulled these workbooks apart, and advanced my Tableau skill set by learning from what others have done. I have developed my method for reverse engineering Tableau workbooks.

I had the opportunity to present this topic at both the 2017 Tableau User Conference and the 2017 Tableau Fringe Festival. These are some of the highlights of that presentation.

Note: a video of the presentation from the TFF will be available soon and will be linked here once available.

What is Reverse Engineering?

Reverse engineering…is the process of extracting knowledge or design information from anything man-made and reproducing it or reproducing anything based on the extracted information. – Wikipedia

Put simply with regards to Tableau, it is the process of taking a workbook, dashboard, or visualization and deconstructing it to understand how it was created so that you can both learn from it and use to recreate in your own visualizations.

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#WorkoutWednesday – 2018 Week 1

This week’s WorkoutWednesday brings to an end the banging my head against the wall at the hands of Andy Kriebel and Emma Whyte. Andy and Emma have decided to take a break from tormenting, err, challenging, us with their weekly exercises. Going forward, the great Rody Zakovich will be taking the reigns. I fully expect more head scratching, mind bending challenges and welcome this new blood to my favorite weekly activity.

This week’s challenge:

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My Tableau Story

I can remember vividly the first time I saw anything done in Tableau. I was working as an Energy Analyst for Honeywell (you know, the guys who make thermostats among all else). One of the sessions I went to was on benchmarking our clients’ energy consumption against others from similar buildings. The two engineers leading the presentation showed dashboards that allowed for interaction and digging deeper into the data. It was simply beautiful and very intuitive.

I was what I would say a self-proclaimed Excel guru. I could do things with a spreadsheet that would make my coworkers heads spin. So you can imagine my intrigue about this presentation. I immediately reached out to the engineers to find out how they created these dashboards. It was then that I first learned their secret was Tableau.

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