Here’s a step-by-step guide to making your very first Tableau dashboard.

In less than an hour, you’ll be able to install the free version of Tableau, add your dataset, create a few charts, and then combine then into a dashboard. You’ll still have time left for formatting, too.

Step 1: Figure Out Which Version of Tableau You Need

There are a few options:

• Public: Free BUT your datasets and graphs will be publicly available.
• Desktop: Paid; about USD $1,000/year per user.
• Server: Paid.

This article compares the versions in more detail.

Step 2: Download Tableau Public

If this is your very first dashboard, I’d recommend starting with the free version, Tableau Public.

Here’s how you’ll install it:

• Visit https://public.tableau.com/en-us/s/download
• Enter your email address and click Download the App.
• The download begins automatically.
• It takes about 5 minutes.

Step 3: Import or Connect Your Dataset

Now, you’ll need to connect your dataset to Tableau.

You can add datasets from Excel, Sheets, QuickBooks, etc.

In this example, let’s pretend we’re visualizing demographic data from an Excel spreadsheet, like this:

Here’s how you’ll add your dataset to Tableau:

• Open Tableau Public.
• Connect to a File: Microsoft Excel. Open your file.
• You’ll see the names of the Excel Sheets on the left.
• Drag in the sheet(s) you want to use for your Tableau dashboard.
• Pre-filter if needed.
• Connect multiple tables if needed. Joins combine the columns of two datasets, and unions combine the rows of two datasets. Joins are most similar to lookup functions in Excel. Unions are most often used when more data is coming in, and you need to add more rows to the bottom of the dataset.

The preview of your spreadsheet will look like this inside Tableau:

Step 4: Drag and Drop Variables to Create One Visual at a Time

We’ll build one chart at a time. Then, in a moment, we’ll combine them into a dashboard.

First, let’s visualize the Work Setting data in Sheet 1. We would drag Work Setting into Rows and Demographics (Count) into Columns. Congrats! You’ve got your first bar chart.

Next, we’ll drag and drop variables to create a Years of Experience histogram.

Finally, we’ll create a color-coded (“choropleth”) map by State.

We’ll create a bar or column chart first, and then simply change it into a map with the Show Me menu.

Step 5: Combine the Sheets into a Dashboard

Now, let’s combine our three individual graphs into a single dashboard.

Here’s how:

• Along the bottom, click on the icon to create a New Dashboard.
• Then, in the Dashboard tab on the left:
  • Choose the device (Desktop, Tablet, phone, etc.).
  • Adjust the size as needed.
  • Drag the Sheets into the main dashboard area.
  • Add Objects as needed (e.g., Blank to add some white space between visuals).
  • The individual graphs can be tiled or floating. I prefer tiled.
  • Check the box to Show dashboard title.

Step 6: Format, Format, Format!

It’s easy to create graphs in Tableau.

Like many software programs, it’s not so easy to format them to be Accessible (508/ADA compliant) and accessible (intuitive).

Here are some bare-minimum edits to get you started.

Apply brand fonts. Go to Format –> Workbook to change all the fonts in your file at the same time (rather than changing one visual at a time). Here’s an article with more info.

Apply brand colors. I personally just go to Marks –> Colors –> More Colors and enter the RGB or HEX codes. Or, here’s an article with a coding option.

I love color-coding by category (i.e., one brand color per graph). This is an easy way to make a dense dashboard feel not-so-dense.

Apply a text hierarchy. Make sure the dashboard title is largest, boldest, and darkest. You’ll also need Heading 1s, and you might need Heading 2s.

As usual, left-aligned text is faster to read then centered or justified text.

As usual, horizontal text is faster to read than diagonal or vertical text.

Don’t forget to turn bulleted tooltips into complete sentences for an extra boost of accessibility.

Your formatted dashboard might look something like this:

Step 7: Share the Dashboard

That’s it! Let’s share it with colleagues.

In the upper left corner, click on File. Choose Save to Tableau Public. Log in. Or, create a username.

Once the dashboard is saved to Tableau Public, you can save the dashboard as an image file, a PDF, a PowerPoint slide, etc.

Learn More

If you’d like to learn more about getting started with Tableau, check out Dashboard Design. This 4-course bundle includes a half-day course on Tableau.

The post How to Make Your First Tableau Dashboard appeared first on Depict Data Studio.

Zach is a Tableau Zen Master and Tableau Ambassador and shared his expertise with us on all things Tableau.  

Watch the Conversation 

About Zach Bowders 

Zach works at JLL, where he’s an external facing consultant who works with countries around the world. Zach is also the creator of the Data + Love podcast and is a Tableau Zen Master and Tableau Ambassador.  

According to Zach, a Tableau Ambassador is a person handpicked by Tableau who’s a super fan that helps promote the brand along with other people’s work while a Tableau Zen Master is a person who showcases the best of Tableau software. Zach has an extensive Tableau portfolio and is one of only 43 in the world (!).  

In his previous career, Zach worked for 13 years at St. Jude Children’s Research Hospital working on the fundraising/giving side. He started in the IT department but then moved into the analytics department where he got his start with Tableau.  

Zach’s Tips on Using Tableau 

First, we talked about Zach’s tips for using Tableau, like sharing visualizations on Tableau Public, his favorite features, features he thinks should be retired, and features he thinks should be added. He also shared some favorite resources and took audience questions.  

Sharing Visualizations in the Tableau Public Gallery 

Zach has over 165 visualizations on the Tableau Public Gallery that he’s created in the past three and a half years.  

Tableau Public is free and Zach says it’s a fun way to share passion projects as well as to get ideas for other projects (personal or business). He said that since so many share projects and make them downloadable, it’s very easy to figure out how they made it and replicate it for another use.  

Zach’s favorite visualization he’s made is about the movie Inception because it doesn’t look like it came from a data software.  

Another favorite is one he created while applying for his job with JLL where he needed to prove how well he knew Tableau. He said, “Having a public portfolio… is very useful for sort of moving ahead in your career.”  

He also noted that none of his visualizations in his public profile were work related, meaning he wasn’t accidentally sharing confidential data or work. He also said that having older stuff in your portfolio that “didn’t age well” shows your growth.  

Favorite Features of Tableau 

Zach said his favorite feature is the drag and drop interface of Tableau. He said that there are a lot of predefined charts that you can quickly create, even if you don’t know all of the rules.  

“I use it as a data exploration tool,” he said. “Sometimes you have a big dataset and you want to know more about it before you make something out of it. It’s very easy to rapidly create exploratory charts to better understand it so then you can make the charts that matter most.” 

Features That Could Be Retired 

Zach said that some of the spacing features in Tableau can take some getting used and that the fields that control where lines and axes can appear on different charts are difficult.  

He said that, “when you’re a newer user, understanding where to find those controls and which ones do what can feel kind of arduous.  So, it’s something you kind of pick up from a little bit of practice or alternatively by popping open someone else’s example and seeing which sort of controls they applied to make things look a certain way.”  

Features That Should Be Added 

“I have lot of things that I’d like,” Zach said. “Copy and paste- it’s not easy to copy and paste a text box or something that you make. If you copy and paste a chart, sometimes if you do it incorrectly, you’ll also apply the same filters from the thing you made. So, the filters now effect both charts instead of each version of it.” 

He also said text options in Tableau are limited to whatever is available on your server, instead of really having all the options that are listed out. He also hopes for some more design features in the future that are more modern.  

Getting Involved with the Tableau Community 

Tableau User Groups (TUGs) 

TUGs are Tableau User Groups and are located throughout the United States. They typically meet monthly or quarterly, have speakers and provide a sense of community to ask questions, learn from others and build a network.  

Zach noted that TUGs are not Tableau run but are rather mostly formed by “impassioned professionals that are trying to help themselves be better or are trying to help other people out.”   

Friendly Competitions, like Makeover Monday, Workout Wednesday, and Sports Viz Sunday 

Makeover Monday is a community exercise where Tableau users get the chance to take a dataset that’s already been visualized but maybe not in the best way and make it over. People then put it on Tableau Public and share it to Twitter or LinkedIn.  

“It’s a great opportunity to on one hand get some practice and also see what other people would do,” said Zach. “If you have the same tool and, in this case, the same dataset, and you see someone else do something that’s better than yours, which you probably will at first, you’re probably going to see like, ‘Wow! Somebody made that?’ Then that’s definitely something that you can make also.”  

Workout Wednesday is a competition where the dataset has already been used to make something technical out of it and you have to figure out how to make the same thing.  

Zach said this comes in handy in work situations where you’re asked to make something out of a dataset and you think, “I don’t know how to do that…” Zach said Makeover Monday is for speed and agility and helps you produce dashboards more quickly. Workout Wednesday is to help you solve more complex problems better.  

Sports Viz Sunday is more sports related dataset and they make lots of interesting stuff Zach said.  

The Datafam 

Zach said datafam is mostly used as a hashtag to gain more attention for Tableau related things online. “But also, it’s the people,” said Zach. “There are a lot of very passionate people out there and typically if you see people using the #datafam, [they’re] sort of the super users that are out there creating the public visualizations, participating in the exercises and a lot of them end up becoming Ambassadors and Zen Masters eventually.”  

Datafam News is a part of Zach’s podcast channel and is hosted by Mark Bradbourne. It is a news update on upcoming TUG meetings, events, and more but Zach said that Tableau is now moving to promote this more officially themselves.  

Tableau Events, like the Conference and Tableau Live 

“Tableau’s conference is a huge deal,” said Zach. It’s attended by over 20,000 and is usually held in Las Vegas, NV due to its size. Tableau Live is the virtual alternative to their in-person conference and offers training and inspiration.  

Podcasts 

Data + Love: https://datapluslove.buzzsprout.com/  

The Tableau Wannabe Podcast (a.k.a. Tableau World Podcast): https://tableauwannabepodcast.libsyn.com/  

“They are the oldest Tableau specific podcast, I believe,” said Zach.  

YouTube 

Tableau Tim: https://www.youtube.com/channel/UC7HYxRWmaNlJux-X7rNLZyw  

“He might be one of the best I’ve seen in terms of tutorials,” said Zach.  

The Flerlage Twins: https://www.youtube.com/channel/UCDyr5VgVvkmfhHpeMUB8ZDA  

“They are twins and both Tableau Zen Masters,” said Zach. “They’re characters as well as very brilliant in what they do.”  

Books 

The Big Picture: How to Use Data Visualization to Make Better Decisions―Faster by Steve Wexler 

“Chapter four is about 80 pages long and it’s a huge, crazy chapter,” said Zach. “It is really like data visualization in a nutshell.” He also said it’s not just for the data professional who’s creating things, but also for the “consumer of data. Because we all have some times [where] we’re the consumers and some times [where] we’re the creators.”  

The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios by Steve Wexler 

Zach said this book is “super influential in terms of the industry.”  

Information Lab – Thursday Trainings @ 3:00  

Information Lab offers free two-hour Tableau trainings that are geared toward beginner, intermediate or advanced users with a Q&A session at the end.  

Zach’s #1 Tip for Beginners Who Are Getting Started in Tableau 

“Just start doing stuff,” Zach encouraged us. “Everyone has probably one hour a week that they can dedicate. So, during that time, I would say, find a blog that you like, watch some YouTube videos or realistically pick one of these exercises. Makeover Monday is an excellent starting place.”  

His final piece of advice was to “make something and share it. Because if you make it yourself and you just sort of hold it back, you’re going to miss out on some of the feedback you’re going to get, which is mostly going to be encouraging. People like to see other people succeed.”  

Connect with Zach Bowders 

LinkedIn: https://www.linkedin.com/in/zachbowders/  

Twitter: @ZachBowders 

Tableau Public Profile: https://public.tableau.com/app/profile/zach.bowders  

The post Navigating Tableau’s Resources with Zach Bowders appeared first on Depict Data Studio.

We sat down at night after our kids were in bed (8 pm for Zach and 9 pm for Ann!) and talked about how to distinguish between IT and data professionals, how to narrow what users *actually* need, understanding your audience and how to speak up when data isn’t useful.

Watch Our Conversation

Listen to the Podcast

Prefer to listen? Download the episode here. 

Distinguishing between IT Professionals and Data Professionals

We discussed an idea Zach brought up in a previous podcast: The difference between a traditional IT role and a data professional.

Those working in the traditional IT role typically receive instructions or a request. Let’s pretend they’re being asked to make a dashboard. Sometimes it’s a specific request with lots of planning, and you can tell the person making the request really thought things through. They might’ve even requested a specific chart type, like “Make a bar chart about xyz topic.”

Those working as a data professional also might receive those requests. The value-add of the data professional is that you’re supposed to push back a little bit. Professionally and respectfully, of course. You read between the lines of what’s requested and then give them what they actually want and need. The value you can add is to ask more questions and dig deeper. You might ask what the data’s going to be used for and what types of actions will be taken based on that data.

Zach added, “A data professional is not more skilled than the IT worker. It’s not to say one is better than the other, just that they’re different roles.”

“You could easily put together something that is technically correct and absolutely worthless,” he explained.

Designing Three Dataviz Ideas to Narrow Down What Users Actually Need

Here’s what I recommend:

• You listen to the request for data. You’re listening, you’re nodding, not interrupting, asking clarifying questions.
• You come up with three ideas. I call these “ideas,” not “makeovers.”
• Idea #1: The original.
• Idea #2: Slightly different.
• Idea #3: Very different. (This is usually the winner, and what people actually need).  

For example, I recently worked I worked with a transportation agency. Their original graph was a pie chart with seven or eight slices representing their revenue sources. It was 3D, had a separate legend, and used tiny font… All of the usual challenges.

Here are the ideas I presented to them:

• Idea #1: An easier-to-read pie chart. We developed a pie chart with one dark slice and the rest grayed out. We also used direct labels in lieu of the separate legend.
• Idea #2: A bar chart to make it easier to compare each revenue source.
• Idea #3: An icon array focusing on how one-third of their revenue comes from ticket sales.

Understanding Who Your Audience Is

Zach and I both agreed that understanding your audience is paramount.

“One of the things I find most important in terms constructing a data viz is your understanding of who the audience is – who is this for?” Zach said. “Because if you don’t know who it’s for, it has to be for everyone. And if it’s for everyone, it’s really for no one. It’s impossible to satisfy all audiences, to bridge all gaps.”

Zach said that people been pictorially expressing ideas for a very long time and that a big part of the process of taking something visual and explaining it to someone is the idea of closure. He explained that, “In the sense that in everything you create, there’s a silent partner that you have (a second creator) which is the audience. So, when you’re constructing your visualization, you and the audience are both pouring meaning into it. You’re not always going to be able to stand next to it, hold their hand and explain exactly what it means.”

He went on to share an example about a grocery store aisle with two-liter bottles. You can see part of the image on each one but you can’t quite see what they are. But it’s enough from your life experience to put together, “Oh! It’s a row of Pepsi logos.” You don’t see a single complete logo, but you can take the incomplete thoughts and knowledge of grocery stores to figure out what it is.

Zach said that this is true of when you’re working on a data visualization project. The people at the organization you’re working with have an understanding of their organization and their data, but also in terms of visual language in general. 

He said that the better you can understand their level of literacy, confidence, and competence with the data, the better you can leverage their own creative ability that they’re bringing to it to figure out what you don’t need to say.

“Part of it is, what you need to bring to it. And the other part is, what can you leave out?” said Zach. “If you’re working on some geographic data and people are wanting to know what sales look like for the United States, what’s the real question they’re asking? Do they really want to see all 50 states? They may, and that may be valid, but if they’re really wanting to see the winners to losers, you may be able to get away with two bar charts showing the top five and bottom five states. That might be exactly what they need. The temptation would be to show all 50 states. They don’t need that. They know there’s 50 states. You don’t have to remind them of that. For the most part, you can leverage many of those ideas as use them as a silent partner to help you get your ideas across better.”

Technical vs. Non-Technical Audiences

One of the most important things to understand about your audience, is not just their titles or roles but whether your audience is technical or non-technical.

A technical audience is people who love data and want to dig deeper into it (both inside and outside of work). They love decimal points and tables. Data isn’t a chore for them. In my experience, this is about 1% of the population.

About 99% of the world is likely non-technical. They don’t like data, find it to be a chore, and would rather do something else. They’re very smart, highly educated, and hard-working, but they have a skill other than data.

If you can identify which you are and which your audience is, you can then recognize when there might be a difference. This helps you determine the right chart type and the right dissemination format. Whether your audience is technical or non-technical informs all design decisions.

Connect with Zach Bowders

Data + Love Podcast: https://www.buzzsprout.com/739517

Twitter: @ZachBowders

The post Listening to What Data Users *Say* They Need… but Giving Them What They *Actually* Need appeared first on Depict Data Studio.

Benefits of Monthly Reports in Large Organisations

Why not just stick with annual reports? Or quarterly reports?

Monthly reports have at least eight advantages over quarterly and annual reports that outweigh the initial costs of automating them.

Data Literacy

Regular, consistently presented monthly reports enable people to become familiar with the terms and parameters used to produce metrics, thereby enhancing their understanding of where an organisation is heading in relation to its targets.

Everyone is on the Same Page

When the same parameters are used for each report the metrics are directly comparable, and everyone is on the same page.

Advanced Warning of Issues that Require Attention

Monthly reports enable potential problems to be detected and addressed early. 

Progress Towards Targets

Monthly reports show readers progress towards targets throughout the year. If metrics are falling behind targets, action can be taken to address the issue. Moreover, if a particular metric is meeting targets, resources can be diverted to prioritising areas that need attention.

Familiarity with Ebbs and Flows of the Year

Monthly reports can inform general patterns throughout the year.

In the example below, the organisation makes most of its sales in the month of July (around 25%) and in December (around 20%).

Generating reports on a monthly basis enables this organisation to estimate that if they haven’t made 50% of their sales by June (i.e. half way through the year) then there is no need to panic until they see the July report when a large peak in sales is expected based on prior years’ data.

Efficiency

In large organisations there are often multiple committees and multiple analysts talking about the same data.

In some cases, producing a report for one department or area of an organisation can require a similar workload to producing the same report across the organisation.

Monthly reports produced for the organisation results in fewer requests for standard metrics from multiple departments. I’ve also received fewer urgent requests as people often refer to the last month’s report if they are in a pinch for data.  

Data Integrity

With many eyes looking at the data on a regular basis, data integrity issues can be picked up early.

It’s a Way To Celebrate Successes

If an area of an organisation has done particularly well during a month it will show up in the visualisations and be a cause for immediate celebration (rather than waiting a whole year).

Similarly, monthly reports provide a timely way to determine if a strategic initiative, such as a new marketing campaign, is working.

How to Choose the Right Metrics for Monthly Reports

You’re ready to make a monthly report! Now what?

It’s important to select metrics that are relevant over monthly time scales when producing monthly reports.

Using student numbers at a fictional educational institution as an example, the student headcount may not change monthly, but the number of student commencements and student completions likely fluctuate as the year progresses.

In this instance, it would be more informative to present information on the number of student commencements and completions in the monthly reports, and then in the annual report present the headcount of the student population. 

An organisation’s annual report should include the metrics that are important but don’t fluctuate throughout the year.

Good Metrics for Monthly Reports: Metrics that Fluctuate Throughout the Year

Not Good for Monthly Reports: Metrics that Don’t Fluctuate Throughout the Year

Good for Annual Reports: Metrics that are Important But Don’t Fluctuate Throughout the Year

Reducing Your Own Workload through Automation

One of the purposes of monthly reports is to reduce your workload.

You don’t want the monthly reports to take days to produce every month, so I recommend choosing metrics that you can automate and have easy access to that do not require a lot of manual processing to produce results, but are still informative.

How to Choose the Right Visualisations for Monthly Reports

Combining data from multiple areas within organisations can produce complex and highly dynamic data sets.

Provide Enough Context: Compare to a Target and/or Compare to the Same Time in Previous Years

It is therefore important to choose types of data visualisation that give readers enough information and context.

This will enable readers to determine whether the organisation or a department is performing better or worse in relation to a target compared to the same time in previous years.

Cumulative Line Charts: My Preferred Method

Cumulative line charts are my preferred method of data visualisation.

These charts enable readers to easily relate previous years data without having to compare among bar charts.

Cumulative line charts also allow readers to easily see troughs and peaks in previous years and how these influence the results.

Visualising Progress Towards Targets

It is useful to include organisational targets to enable readers to easily compare them to the data.

Progress towards targets can be visualised in several ways.

Pie and donut charts are probably familiar to most readers or reports and can be used in certain circumstances.

See Ann’s post on the seven guidelines for using pie and donut charts and for alternatives to pie charts.

Below is a waffle chart as an example of an alternative to a pie chart.

Ask for Feedback from Your End-Users

I’ve received great feedback, tips and ideas from the end-users of the data. End-users are coming at your report with fresh eyes and they are the ones that have to use the information at the end of the day, so it’s worth incorporating their feedback if you can.

Better yet, take the Great Graphs online course and find out more. I did, and I haven’t looked back.

Share Your Tips for Monthly Reports

Have you got any tips for monthly reports? Does your organisation use them? Share your thoughts below!

The post Why Your Organization Needs Monthly Reports appeared first on Depict Data Studio.

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If you’re like me, you were probably inspired to revise some of your charts after reading Ann’s How to Visualize Age/Sex Patterns with Population Pyramids. Too often when I storyboard demographic information I default to separating out this demographic information (you know, for the sake of keeping things simple). Unfortunately, this is sometimes a missed opportunity to provide a more comprehensive picture. These things combined inspired me to recreate the Pyramid Chart in Tableau — Let’s get started!

The Data

The dataset we’ll be using is from the Arizona Office of Economic Opportunity, which you will see consists of age groups, sex (male/female), and population. If you receive disaggregated data, that wouldn’t be a problem — that’s Tableau’s specialty!

The Hack

We want to load our data source, review that our variables came in correctly, and add a new sheet. Next, we’ll drag two Population pills to Columns.

Now drag Age Group to Rows. You will want to click the arrow and uncheck Show Header.

To get our Age Groups in the middle, we need to hack Tableau a bit. Start by creating a Middle calculated field — all you’re doing is entering “0” and saving. Next, drag the Middle pill between your Populations. On the Marks Card, add Age Groups as a text item and change the type to text.

Okay, we’re making progress! Realizing our pyramid (or butterfly) is dabbing, we need to reverse the axis of our population on the left.

Note: You might need to sort Age Groups, as I did (see above where Under 5 years is after 85 years and over).

In order to highlight females on one side and males on the other, we need to create a couple calculated fields.

On the Marks Card, add Female as a text item to one population and Male to the other. Now we have the shape of something, but you probably noticed that the comparison is about as helpful as a table.

To change that, we’re going to get crafty with colors and create a calculated field for each. This will allow us to control the colors independent of one another while still maintaining the same x-axis (i.e. Population).

After creating your Female/Male Color calculated fields, you’ll want to drag them to their respective Color Marks Card. Next, edit the colors and be sure the “0” (i.e. the sex you don’t want to call out) is something very light.

Additional color tips: You’re better than basic — use something other than the default blue and orange Tableau gives you. You should also avoid using traditional blue and pink to represent male/female (this is 2018, after all!).

Our final steps will be cleaning up our visual. First, I want to get rid of unnecessary borders and lines across the entire sheet (they’re just a distraction). I would also hide my axes, as I have labels on my bars.

Speaking of the labels, I want to format (SUM)Female/(SUM)Male to be a nice round number and change my units to thousands (K). You should use your discretion when doing this but for the purpose of this chart, I know my readers aren’t actually distinguishing between 200,010 and 200,500.

Last but definitely not least, I want a descriptive title that pulls readers in. You’ll notice that I also leveraged colors in my title to differentiate between each side of the pyramid.

Bonus: You can go the extra mile and include some great information in your tooltips, too. Often, percentage of an entire population is a really important piece of information. The tooltip is a great way to provide that without adding distractions to the visualization.

The post How to Visualize Age/Sex Patterns with Population Pyramids in Tableau appeared first on Depict Data Studio.

Tableau dashboard ideas often originate from new and interesting data or conversations with those using your data. At the National Association of State Arts Agencies (NASAA), we talk with our members often to understand their needs and what is most important to highlight in a visualization. Ideas are plentiful and roadblocks to implementing your ideas can be just as frequent. Here are some tips from our organization’s experience using Tableau to generate interactive visualizations for state agencies.

Tip #1: Select the Appropriate Level of Detail

Before making visually appealing charts, you need to decide how to showcase your data for maximum benefit to your end users.

Familiarity with the data can be a disadvantage. How you use raw data on the backend may not necessarily translate to how people want to view data on a Tableau dashboard. Parameters, calculated fields, or groups will help deliver the type of analysis your users need.

Consider the level of detail to showcase. Will you display data for individual grants, organizations, cities, regions, or states? Some users may prefer a very detailed unit level. Others might just want to see aggregated figures. For instance, our users might not want to see each grant administered from every agency across the country. It might be more meaningful to show medians, means, or percent of total by state or region.

Note: When you are getting started and using data from an Excel sheet, your dataset may not be optimally shaped for Tableau use. Luckily, there is an Excel plugin that will shape data for Tableau–it’s faster than making a pivot table or using the Tableau Data Interpreter!

Tip #2: Don’t Be Tempted by Flashy Chart Types

Tableau’s “Show Me” function will display a plethora of assorted, flashy charts to choose from.

When in doubt, go with bar and line graphs. These simple chart types are still how many people can relate to visualized data, and chances are your end users are not mathematical physicists expecting four-dimensional graphs. You can use exciting bubble and tree charts ONLY if they really are the most effective at conveying the information.

Additionally, be prepared to make a lot of bad graphs to get a great one. If it’s part of your creative process, make a few charts that look like rainbow spaghetti and then edit them down to palatable visuals. Our process usually starts out with outside-the-box visualizations before selecting a few good formats.

A little too outside-the-box… to a clean bar graph that is easy to read.

Tip #3: Minimize Distractions by Building Symmetrical, Aligned Visualizations

Your dashboard may end up with some odd spacing between titles and subtitles, or between charts. Taking a step away from the dashboard will help you see where formatting oddities draw the user’s eye and try to minimize the distractions from the data.

Hack your layout. Adding 8-point spaces between titles and tiny spacing boxes next to charts can be onerous, but it will make the visualization look more streamlined and well put together.

Left: Note how the spacing is asymmetrical and how the subheading gets a lost. Right: More symmetry and space between the heading and subheading makes it easier for the eye to read.

Tip #4: Add Context with Tooltips

Give the data context by writing a sentence with tooltips.

When users hover over your visualization with their mouse, then they’ll see your sentences in little pop-up boxes, like this one:

Are you displaying a calculated field, like percent change over time, but also want users to have access to the actual figures? Tooltip.

Want to associate more data with dots on a map? Tooltip.

Need to define a term? Tooltip.

Sometimes Tableau automatically generates tooltips, so practice good tooltip hygiene on all your charts.

You can get some quick ideas for how to incorporate tooltips by visiting one of NASAA’s suite of visualizations.

Tip #5: Design for Both Web and Print

We know a lot of our members like working with visualizations online. But many users also like to print dashboards out for meetings.

We try to make the size of the dashboards amenable to a standard sheet of paper. We also ask ourselves if all the data people need to see are visible from a printout. In other words, is there information inside Tableau’s tooltips that needs to be shown in the dashboard itself?

If your users are viewing dashboards on mobile devices, then make sure to use the mobile design function.

Tip #6: Use Minimal Formatting

When in doubt, get rid of extraneous lines, tick marks, and boxes in and around charts. The extra stuff crowds the data you want people to focus on. Plus, minimal formatting just looks clean and polished.

Left: Data can get lost with extraneous lines. Right: Without extra tick marks and grids you can see data more clearly.

Tip #7: Choose Your Colors Wisely

Highlight important data points with something bright, but try not to physically hurt people’s eyes with a neon green.

Have in mind the larger context/visual environment in which the dashboard will be viewed. If it will be embedded on a website, it should not clash with the web design.

If people external to your organization will be seeing it, consider how to incorporate your branding.

If you know people will print a dashboard, remember that most print in black and white, so make sure the hue values are differentiated enough to be distinguishable in grayscale.

Make sure that colors of different hue values will still show clearly when printed in black and white.

We hope these tips serve as a starting point to help evolve your visualization practices!

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