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Thank you for your question! This is what "Viz Talk" is all about - sharing ideas and perspectives about visualizations.
As you say:
there seems to be no definitive right or wrong answers when designing a dashboard or interactive report.
This is because there are probably as many answers as there are people with opinions.
My opinion is very similar to that of Justin Meyer in his book Plain Talk about Fine Wine, regarding whether a wine is "good" or "bad." In short, if you like it, and it does the job for which it is intended, don't worry about other people's opinions.
That said, I am always learning how to improve my data visualizations by reading books, especially those of Stephen Few, watching videos, reading blogs, etc. Each person's viewpoint offers me a new perspective that can make my output more useful to others. So, I will offer a few of the high points here, along with some comments on how they apply in your case above.
- Consider the audience. By "audience," I mean the users of your visualization. Include in this their level of training in data interpretation, their role, their goal in viewing the viz, the size of the audience, the size of the venue, etc. The broader the audience, the more difficult it is to make one viz work for everyone. It is much easier to create a specialized viz for a small highly trained audience who are using it individually, than it is to present to a large group in a large venue. In your case, if you are targeting the first group (small, highly trained), then I if it meets their needs, you are spot-on. On the other hand, if you are presenting this to executives in a board room, you will lose them in 5 seconds.
- Use the right tool for the job. Tableau is the right tool for most interactive visualizations. Tableau is probably not the right tool for downloading a large tabular report. If, by "interactive," you mean that selecting data in the charts filters and/or highlights data in the other charts and in the "Details," I think you are on the right track. If your goal is for people to download the "Details" section, I have doubts, but it could be okay.
- Tableau has 3 viz categories: sheets, dashboards, and stories. The Tableau functional definition of a "dashboard" is much broader than Stephen Few's definition of "dashboard," which is "a tool for at-a-glance monitoring." An interactive tool such as yours falls outside Stephen Few's definition. Lacking a better word, I call these "analyzers." (I would love to see other suggestions.)
- You mention that you did not see a need for colors. Since you hid nearly all the visual aspects of the viz, it is difficult to say whether I would agree or disagree. However, I will say that I rarely find vizzes that would not be in some way enhanced by color. Color can indicate values, drawing the eye to the most important, or it can help tie together similar categories in various parts of the viz, reducing the effort of user interpretation.
I would like to comment further, but, again, you hid so many aspects of the viz, there isn't much left to comment on. I would encourage you to attach an anonymized packaged workbook (see Packaged workbooks: when, why, how ).
Thanks for taking time to respond, Bill. This is incredibly helpful. You have clearly drawn a distinction between "Analyzers" and "Dashboards". Given how easy it is to build a data product in Tableau, but it takes a whole new set of skills/ third eye/ elevated spiritual senses to bring together a very useful product that serves a set of "audience" . As this effort all along requires us to build consensus, as everyone seems to want different things. Also they always seem to ask to add more information, than less information on screen. Our users are operational level, but a good part of them are not highly technical, so, bringing consistency in user interactions, and layouts are a top priority as well. We can't use different types of date filters, because, users would find it confusing to see a 'Range filter' vs 'Relative date filter' vs a 'Parameter filters'; or a smart filter that displays only 'relevant values' vs use cases where relevant values are not going to meet their needs. Decisions decisions decisions. I have not read any of the books you have mentioned, and I think I am going to get a copy and start on them. Unfortunately I am unable to attach a workbook at this time. I will try to anonymize and see if I can post one.
Thanks again for explaining it well, Bill. Very helpful!!