In visual analytics, data interaction can be as important data visualization. This tutorial is about adding interactivity to Tableau visualizations, specifically using Filters and Parameters. Filters Filters, you guessed it, let you filter data. In Tableau, they can be either static or interactive. An example of a static filter would be a condition that was set in worksheet mode to display a certain subset of the total data (eg. only.]]>
In visual analytics, data interaction can be as important data visualization. This tutorial is about adding interactivity to Tableau visualizations, specifically using Filters and Parameters.
Filters
Filters, you guessed it, let you filter data. In Tableau, they can be either static or interactive. An example of a static filter would be a condition that was set in worksheet mode to display a certain subset of the total data (eg. only sales for certain provinces, or certain product categories). Static filters can be revised in the worksheet by going back to the original filter dialog, but can’t be changed in dashboard mode or from Tableau Public. In other words, they are not interactive by default. You can make them interactive, however, by choosing Show Quick Filter to add a filter list to the worksheet and dashboard.
Parameters
Parameters are commonly used to create additional types of interactive filters, but they are not, in themselves, filters. Rather, they are variables. As such, they aren’t really useful on their own; they have to be part of something else, such as an equation, a filter, a reference line, a calculated field, or what Tableau calls parameter controls (sliders, selection menus and type-in fields).
Like filters, parameters can be either static or interactive. An example of a static parameter would be a fixed sales target that is used in a bar graph to colour sales numbers that meet the target one colour, and those that don’t, another. An example of an interactive parameter would be a parameter control slider on the dashboard that lets the user adjust the sales target up or down and see the resulting colour change in the visualization.
As an interaction designer, I think of sliders, selection menus and type-in fields in terms of interaction. Tableau, on the other hand, is more concerned with the underlying math, formulas and analysis. As a result, the workflow in Tableau for creating interactivity starts with the parameters and calculated field formulas first, and adds the interactive feature to the UI last. Secondly, interactive features are called “Parameter Controls”, suggesting that you are interacting with the underlying formula more so than the visualization itself.
Personally, I find Tableau’s workflow is a bit counter intuitive. Here’s how I would do it: add an Interactions Card to the standard worksheet UI. Populate the card with icons for sliders, selection menus, radio buttons, toggle switches, zoom tools, selection tools, reference lines etc. This way, the user can simply drag an interaction icon to a visualization, or drag a measure or dimension to the interaction icon first; and then establish the parameters of the tool second. I feel like this drag and drop approach would be intuitive and still consistent with Tableau’s other workflows. Anyway, that’s my two cents’, for what it’s worth.)
Tutorial
The following examples illustrate different ways to use Filters and Parameters. Once again, I’m using the SuperstoreSales data found here
. Open a new worksheet tab for the first two examples because we’ll come back to them in the second half of the tutorial.
Filters
Probably the most familiar and straightforward filter type is the simple filter.
Filter by top (or bottom)
Open a new worksheet tab. Say you wanted to look at Sales for every individual product the Superstore sells.
Filter by top and condition
In a slightly more complex scenario, what if you wanted to look at the top 15 sellers in the Technology Product Category?
In plain english, this formula means: for each product order (i.e. row in the dataset), IF the product category is Technology, THEN add the Sales amount; if not, add zero. Tableau will confirm that your syntax is correct with a green check mark or tell you there’s something wrong with a red X. Assuming the syntax is correct, click Apply, then OK at the bottom of the CF dialog. Then click OK again at the bottom of the Filter dialog.
Parameters
The examples so far have used static filters (i.e. fixed, under the hood). They can be revised in a worksheet by reopening the Filters dialog and revising the filter, but they can not be adjusted or interacted with in a dashboard. The following examples illustrate how Parameters can be used to make them more interactive.
Add an interactive filter list
It doesn’t actually take a Parameter to make a filter list interactive. All you have to do is right click on the filter name in the Filters card and select Show Quick Filter. Tableau will add an interactive filter list to the worksheet.

Add a slider control
Using the Filter by top example, say you want to replace the fixed number of products to display (15) with a slider that lets user control how many top (or bottom) selling products to display. To do this you need to revise the original Product Name Filter from a fixed number (15) to a variable using a Parameter.
Add a Reference line
Use the same Filter by top technology sales example again. This time, say you wanted to add a Reference line that showed a sales target, and you wanted to make that reference line adjustable by the user.
Parameter + CF (Big market/small market cutoff example)
A parameter can also be used in a calculated field. For example, say you wanted to look at Sales by Province and categorize the provincial markets as either big or small depending on the number of sales. Since the big market/small market designation is not part of the original dataset, we have to use a Calculated Field to create it. In this case, lets look at the number of sales orders, as opposed to either tthe order quantity (i.e. 50 pens or 10 desks) or the sales value (i.e. dollar value).
In plain english, this formula says is: IF the count (i.e. the number) of Sales is greater than 500, THEN it is a Big market, otherwise it is a Small market.
Tableau will verify that the formula syntax is correct with a green checkmark below the Formula window. Then click OK to close the dialog.
DataViz in 6 Weeks is my blog about teaching Introduction to Visual Analytics at OCAD University in Toronto. Comments, follows and shares welcome. #DataVizInSixWeeks
Anne Stevens
I am a multidisciplinary designer working in data visualization, interaction design and innovation. I am particularly interested in non-screen based physical representations of data and tangible user interfaces.
Tableau v9.0 virtual launch party overFLOWs with marketing jargon Tableau hosted an east-coast/west-coast Virtual User Group launch party to introduce their newest version, v9.0: the Flow release, as they coined it. __ First impression At the risk of sounding shallow, I expected a bit more polish from Tableau. They are a worldwide leader in the BI market and they boast impressive revenue and growth numbers. But with too much blunt.]]>
Tableau v9.0 virtual launch party overFLOWs with marketing jargon
Tableau hosted an east-coast/west-coast Virtual User Group launch party to introduce their newest version, v9.0: the Flow release, as they coined it.
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First impression
At the risk of sounding shallow, I expected a bit more polish from Tableau. They are a worldwide leader in the BI market and they boast impressive revenue and growth numbers. But with too much blunt marketing jargon and filler the two hour production seemed a bit cheap.
I couldn’t resist counting the number of times (a) Flow, Where Smart Meets Fast, Instant Analytics and Fast Fast Fast were use, (b) improved user experience was referenced, and (c) one of the presenters repeated the mantra: “I’m so excited!!!”. Which begs the question: why wasn’t there more content for this invested and engaged Tableau user to focus on?
So just how many times was the word FLOW used in the just-less-than-two-hour event? Answer: 25. See the viz above.
Which presenter used it the most? Answer: that depends. Ellie and Elissa each used it twelve times. So, based on the raw data, it’s a tie. However, normalizing the data reveals Elissa as the front runner, using Flow every 55 seconds on average. By comparison Ellie, who was on air much longer, only used it every 3 minutes and 50 seconds, on average. Congratulations Elissa.

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Enough about the talking heads. Let’s get down to the new Tableau product itself. This is what v9.0 has to offer:
For the data geek
Lots and lots of geeky new stuff:
For the mapper
Improved usability (thank goodness!!!)

I didn’t hear anything about improved map granularity for non-US locations. However, Ellie’s map example – Edinburgh, Scotland – had postal-code/zip-code level detail, so I’m optimistic.
For the interface and usability person (and who isn’t?)

For the Tableau Public user
Apparently all the new v9.0 features will be available on Tableau Public, not just the paid versions (Server, Online and Desktop).
Tableau claims that they will be adding more profile and social features to TP so that people can use the platform more as a portfolio and blog. I hope they offer some control over who can see what. For example, I might want to publish my finished works to everyone, but hide all my drafts and preliminary versions. Or, I might want to share visualizations amongst a certain group of people – my Visual Analytics class, for example. Hopefully, that will be possible. Tableau didn’t provide this kind of detail, so it remains to be seen.
For the storyteller
Ellie mentioned formatting upgrades for Storypoints – not during her formal demo, but as more of a casual comment during her chit chat with Nate in the dying minutes of the production. She suggested these upgrades could be a sleeper hit of v9.0, but didn’t offer any additional details or images. Stay tuned.
For sales and marketing
A lot of cheese during the sales pitch part of the presentation:

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Background
I use Tableau Public and Google Refine (aka Open Refine) in my Introduction to Visual Analytics course so that the students can get up and running in a relatively short time generating multiple visualizations from real datasets. At this point in time we use Tableau Public v8.2 for Mac.
I have not personally beta tested v9.0. This blog is based solely on what I heard and saw during the Tableau Virtual User Group launch party. I look forward to using v9 after its full release and am sure that I will discover much more then. Stay tuned.
Oh, and one more thing: did I mention flow?
DataViz in 6 Weeks is my blog about teaching Introduction to Visual Analytics at OCAD University in Toronto. Comments, follows and shares welcome. #DataVizInSixWeeks
Anne Stevens
I am a multidisciplinary designer working in data visualization, interaction design and innovation. I am particularly interested in non-screen based physical representations of data and tangible user interfaces.
I created this data viz course and have delivered it four or five times now. As you might imagine, I didn’t get everything right the first time (“no guff!” I hear the first cohort saying) and, as a result, the course evolved from one iteration to the next. I have learned a thing or two about teaching along the way. The students in Continuing Studies are already pretty highly motivated.]]>
I created this data viz course and have delivered it four or five times now. As you might imagine, I didn’t get everything right the first time (“no guff!” I hear the first cohort saying) and, as a result, the course evolved from one iteration to the next.
I have learned a thing or two about teaching along the way. The students in Continuing Studies are already pretty highly motivated self starters. Why else would they commit their Saturdays or Sundays to data viz school? Nevertheless, this time around I deliberately increased their deliverables and structured weekly assignments of one kind or another. Wow! Did they ever deliver. Mind blown : )
As an homage to @thisisindexed.com, I captured my biggest take-away from the class in a simple info graphic: the more you ask them to do, the more they deliver.
DataViz in 6 Weeks is my blog about teaching Introduction to Visual Analytics at OCAD University in Toronto. Comments, follows and shares welcome. #DataVizInSixWeeks
Anne Stevens
I am a multidisciplinary designer working in data visualization, interaction design and innovation. I am particularly interested in non-screen based physical representations of data and tangible user interfaces.